HK1215732B - Method and apparatus for performing and quantifying color changes induced by specific concentrations of biological analytes in an automatically calibrated environment - Google Patents

Description

Method and apparatus for performing and quantifying color changes induced by specific concentrations of biological analytes in an automated calibration environment

Cross-reference to related applications

This application claims the benefit of U.S. Provisional Patent Application No. 61/680,842, filed August 8, 2012, entitled “Multi-Analyte Rapid Diagnostic Test and Method of Use,” which is hereby incorporated by reference in its entirety.

Technical Field

The present invention generally relates to systems and methods for detecting the presence or absence of multiple analytes in a fluid sample using a diagnostic instrument, and in particular, for determining diagnostic test results through image analysis of digital images of the diagnostic instrument.

Background Art

Dipsticks and immunoassays have been used in medical clinics for decades as a method for rapidly diagnosing health conditions at the point of care. In clinical settings, dipsticks have been used to diagnose urinary tract infections, preconvulsions, proteinuria, dehydration, diabetes, internal bleeding, and liver problems. As is well known, dipsticks are laminated sheets of paper containing a reagent that changes color when exposed to an analyte solution. Each reagent test pad on the dipstick is chemically treated with a compound known to change color in the presence of a specific reactant. For example, in the case of urinalysis, the dipstick will typically include a reagent pad for detecting or measuring analytes present in a biological sample such as urine, including glucose, bilirubin, ketones, specific gravity, blood, pH, protein, urinary bilirubin, nitrite, white blood cells, microalbumin, and creatinine.

The magnitude of this color change is proportional to the analyte concentration in the patient fluid. Test strips are typically interpreted visually by comparing the test strip to a colored reference card. However, such color comparisons can cause user confusion and error for several reasons, including changes in ambient lighting and the fact that color vision is impaired in most people.

Automated methods and apparatus for interpreting test results of test strips and immunoassays that have been exposed to a sample solution are known in the art. For example, U.S. Patent Application Publication No. 2012/0063652 to Chen et al. (hereinafter referred to as the "'652 Publication") discloses a method for performing a color-based reaction test on a biological material, but in an uncalibrated environment, specifically by capturing a digital image of a test strip and a color reference card side by side in a single image. The test result of the test strip is automatically obtained by performing a simple color match between the reaction area of the test strip and the color reference card to determine the analyte concentration of the biological material.

When using the method disclosed in the '652 publication, the user must properly align the test strip and the color reference card before capturing a digital image. Thus, the user must contact the exposed test strip after it has been contaminated with a biological sample, such as urine, blood, or stool, and position it in the proper position relative to the color reference card. Therefore, to assist in positioning the test strip and/or card, automated interpretation equipment often includes additional positioning elements, such as a box or felt paper, to position both the test strip and card in the correct orientation.

In view of the problems existing in currently available methods for automatically reading test strips, there is a need for an automated testing method that uses a digital image captured in an uncalibrated environment. The system or method should be configured to automatically calibrate the digital image to correct for any color deficiencies, artifacts, or other ambiguities. The method should also automatically identify the relevant portions of the digital image, regardless of how the test strip and/or color reference are positioned in the digital image. Finally, the method should minimize the manipulation of samples contaminated by biological fluids. The methods and systems of the present invention address these deficiencies of known automated detection devices, systems, and methods.

Summary of the Invention

A method and electronic user device for performing a quantitative assessment of the color change induced by exposing multiple test strips to biological materials/fluids is generally provided. Preferably, the system and method provided allow for automatic calibration of digital images of multiple test media exposed to sample solutions to determine whether certain analytes are present in the sample solutions. More preferably, the present invention provides a method and electronic user device for quantifying the color change induced in various test strips by exposure to samples. This quantification is based on an automatic calibration protocol, independent of changes in the external environment. The present invention produces accurate, precise and cost-effective measurements while minimizing user interaction with biological samples. This method is designed to support medical scientific instruments that comply with FDA and EU regulations in areas intended to minimize errors.

Thus, according to a preferred and non-limiting embodiment of the present invention, a computer-implemented method for quantifying color changes of at least one test medium on a diagnostic instrument is provided. The method comprises the step of capturing a digital image of at least a portion of a diagnostic instrument that has been exposed to a biological sample. The diagnostic instrument comprises at least one color reference comprising a plurality of reference samples of different colors and at least one test medium containing a reagent that changes color in the presence of a specific analyte in the biological sample. The method further comprises the steps of: identifying at least one of the reference samples used for the at least one medium in the diagnostic instrument; determining the apparent camera-captured color of the reference sample and the apparent camera-captured color of the at least one test medium; color-correcting the apparent camera-captured color of the at least one test medium based on a correction factor derived at least in part from the apparent camera-captured color of the reference sample to determine a corrected test medium color; and comparing the corrected test medium color to a set of possible test medium colors corresponding to a predetermined analyte concentration to determine a test result comprising the analyte concentration of the biological sample being tested.

According to another embodiment of the present invention, a computer-implemented method for determining a relative position on a diagnostic instrument includes the steps of capturing a digital image of at least a portion of the diagnostic instrument that has been exposed to a biological sample. The diagnostic instrument includes at least one test medium containing a reagent that changes color in the presence of a specific analyte in the biological sample. The method further includes the steps of: scanning the digital image to identify the location of a predetermined area on the diagnostic instrument; identifying the at least one test medium on the digital image based at least in part on the location of the predetermined area; and determining a test result by comparing the color of the at least one test medium to a set of possible test medium colors corresponding to predetermined analyte concentrations to determine the analyte concentration of the biological sample being tested.

According to another embodiment of the present invention, a method for validating a diagnostic instrument includes the steps of capturing a pre-use digital image of at least a portion of the diagnostic instrument before exposing the diagnostic instrument to a biological sample. The diagnostic instrument includes at least one color reference comprising a plurality of reference samples of different colors and at least one test medium containing a reagent that changes color in the presence of a specific analyte in the biological sample. The method further includes the steps of: identifying the at least one test medium in the pre-use digital image of the diagnostic instrument; comparing the color of the at least one test medium to a set of possible test medium colors of the reagent that has not been exposed to the analyte; and determining whether the diagnostic instrument is in a condition for use based at least in part on the color of the at least one test medium.

According to another embodiment of the present invention, a diagnostic instrument for identifying multiple test results by testing a single patient fluid is provided. The instrument comprises: an instrument housing; a color reference comprising a plurality of reference samples of different colors, attached to or associated with the housing for use in determining the test results from a digital image of the diagnostic instrument; and a plurality of test media attached to the housing, containing a color-changing reagent that changes color in the presence of a specific analyte in the biological sample.

According to another embodiment of the present invention, a system for reading diagnostic test results is provided. The system includes: a diagnostic instrument; and a portable electronic device having a camera sensor and a processor for capturing a digital image of at least a portion of the diagnostic instrument. The diagnostic instrument includes a color reference having multiple reference samples of different colors and multiple test media containing reagents that change color when a specific analyte is present in a biological sample. The processor of the portable electronic device is configured to: identify at least one of the reference samples and at least one of the test media on the digital image of the diagnostic instrument; determine the apparent camera-captured color of the reference sample and the apparent camera-captured color of at least one test medium; color correct the apparent camera-captured color of the at least one test medium based on a correction factor derived at least in part from the apparent camera-captured color of the reference sample to determine a corrected test medium color; and compare the corrected test medium color with a set of possible test medium colors corresponding to a predetermined analyte concentration to determine a test result including the analyte concentration of the tested biological sample.

According to another embodiment of the present invention, a portable electronic device for analyzing digital images from a diagnostic instrument is provided. The diagnostic instrument includes at least one color reference for a plurality of reference samples having different colors and at least one test medium containing a reagent that changes color in the presence of a specific analyte in the biological sample. The portable electronic device includes at least one processor; at least one display device; at least one camera sensor (digital image capture device); and at least one computer-readable medium containing program instructions. When executed by the at least one processor, the program instructions cause the portable electronic device to: capture, with the camera sensor, a digital image of at least a portion of the diagnostic instrument that has been exposed to a biological sample; identify at least one of the reference samples for the at least one medium in the diagnostic instrument; determine an apparent camera-captured color of the reference sample and an apparent camera-captured color of the at least one test medium; color correct the apparent camera-captured color of the at least one test medium based on a correction factor derived at least in part from the apparent camera-captured color of the reference sample to determine a corrected test medium color; and compare the corrected test medium color to a set of possible test medium colors corresponding to a predetermined analyte concentration to determine a test result that includes the analyte concentration of the biological sample being tested.

These and other features and characteristics of the present invention, as well as the methods of operation and function of the related structural elements and the combination and manufacturing economy of the various parts, will become more apparent after considering the following description and the appended claims with reference to the accompanying drawings, all of which form a part of this specification, wherein like reference numerals refer to corresponding parts in the various figures. However, it is to be expressly understood that the drawings are for illustration and description purposes only and are not intended as a definition of the limits of the present invention. Unless the context clearly dictates otherwise, as used in this specification and claims, the singular forms "a," "an," and "the" include plural referents.

BRIEF DESCRIPTION OF THE DRAWINGS

For the purpose of promoting an understanding of the invention, the drawings and description illustrate preferred embodiments thereof, from which the invention, its various embodiments, constructions, and methods of operation, together with its numerous advantages, may be understood and appreciated.

FIG1 is a top view of one embodiment of a diagnostic instrument according to the principles of the present invention;

2 is a schematic diagram of one embodiment of a system for analyzing a biological sample using the diagnostic instrument of FIG. 1 in accordance with the principles of the present invention;

3 is a flow chart of an embodiment of a method for capturing an image of a diagnostic instrument;

4 is a flow chart of an embodiment of a method for determining a patient condition from a digital image of a diagnostic instrument in accordance with the principles of the present invention;

FIG5 is a schematic diagram of a Manufacturing Interpretation Color Chart (MICC) for urine analysis known in the prior art;

6A through 6D are photographic representations of diagnostic instruments with markings indicating the orientation of the instrument in the photograph relative to the x-axis, y-axis, or z-axis.

7A through 7C are schematic representations of enlarged views of a color test pad containing background artifacts as identified by the geometric correction calculations of the method of FIG. 4 ;

FIG8 is an enlarged photographic representation of a reference color bar as identified by the geometric correction calculations of the method of FIG4;

FIG9 is a schematic diagram of a process for color correcting a digital image of a chemical test pad in accordance with the principles of the present invention;

FIG10 is a schematic representation indicating the mapping of color samples from a manufacturing interpretation color chart into a red-green-blue (RGB) color space;

FIG11 is a schematic diagram of the RGB color space of FIG10 including color samples from MICC and calibrated test medium colors;

FIG12A is a schematic diagram of an RGB color space including a color locus derived from a MICC color sample and a corrected test medium color;

FIG12B is an enlarged schematic diagram of the color trajectory of FIG12A;

FIG13 is a photographic representation of a manufacturing interpretation color chart with identified test results;

FIG14 is one embodiment of a decision tree for identifying patient conditions associated with leukocytosis in urine in accordance with the principles of the present invention;

FIG15 is one embodiment of a decision tree for identifying patient conditions associated with increased proteinuria in accordance with the principles of the present invention;

FIG16 is a flow chart of an embodiment of a method for capturing an image of a diagnostic instrument in accordance with the principles of the present invention;

17 is a schematic diagram depicting a table of minimum and maximum color change values for a plurality of chemical test pads for use in validating a diagnostic instrument in accordance with the principles of the present invention; and

FIG. 18 is a schematic diagram of a computer and network infrastructure according to the prior art.

DETAILED DESCRIPTION

For descriptive purposes hereinafter, the terms "upper," "lower," "right," "left," "vertical," "horizontal," "top," "bottom," "lateral," "longitudinal," and their derivatives shall refer to the actual orientation of the invention in the accompanying drawings. However, it should be understood that the invention may employ alternative variations and step sequences, unless expressly specified to the contrary. It should also be understood that the specific devices and processes illustrated in the accompanying drawings and described in the following specification are merely exemplary embodiments of the invention. Accordingly, specific dimensions and other physical characteristics with respect to the embodiments disclosed herein should not be considered limiting.

As used herein, the term "communication" refers to receiving or transmitting one or more signals, messages, commands, or other types of data. When a unit or component communicates with another unit or component, it means that the unit or component is able to directly or indirectly receive data from the other unit or component and/or transmit data to the other unit or component. This may refer to a direct or indirect connection that may be wired and/or wireless in nature. In addition, two units or components may communicate with each other, even if the transmitted data may be modified, processed, and/or routed between the first and second units or components. For example, a first unit may communicate with a second unit, even if the first unit passively receives data and does not actively transmit data to the second unit. As another example, if an intermediate unit processes data from one unit and transmits the processed data to a second unit, the first unit may communicate with the second unit. It should be understood that many other arrangements are possible. Components or units may be directly connected to each other or may be connected via one or more other devices or components. The various coupling components for the devices may include, but are not limited to, the Internet, wireless networks, conventional cables, fiber optic cables, or connections via air, water, or any other medium that conducts signals, and any other coupling devices or media.

The present invention relates to diagnostic instruments, systems, and methods for testing patient fluid samples that can be used in a clinical setting or for home use. More specifically, the present invention relates to performing color-based reaction tests on biological materials in an automated calibration environment. Preferred embodiments of the present invention are implemented as applications running on portable electronic devices, such as cellular phones, tablet PCs, computers, laptop computers, or other dedicated electronic devices. The methods have been designed to minimize user contact and manipulation of biologically contaminated samples. Error prevention and compliance with medical device regulations have been implemented at all levels in the design of the protocol. Specifically, the invented methods have been designed to avoid modification, damage, and discarding of original data.

Diagnostic instruments are configured to provide rapid detection of patient conditions using test strips, such as reagent test strips. Test strips are typically narrow strips of plastic or paper that contain certain reagents or antibodies that serve as recognition elements for detecting a given analyte or disease marker in a patient fluid sample. Often, the intensity of the color change of the test strip is indicative of the concentration of the analyte or disease marker in the patient fluid. Patient fluids may include urine samples, blood samples, patient cells in a fluid solution (e.g., cells obtained from a throat swab), semen, mucus, blood, saliva, and the like.

The diagnostic instrument is configured to test patient fluid samples for a variety of diseases and patient conditions to increase the likelihood that multiple conditions can be identified during a testing session. Thus, the user does not need to select which test to perform or the order in which the tests should be performed. In one non-limiting preferred embodiment, the diagnostic instrument can test for pregnancy and pregnancy complications, such as preconvulsions.

With reference to FIG1 and in a preferred and non-limiting embodiment, a diagnostic instrument 10 is provided, which includes a paddle 12 for holding at least one test strip 14. The paddle 12 includes a handle 16 and a test area 18 adapted to hold multiple test strips 14. The test area 18 includes a plurality of indentations 20 for holding at least one individual test strip 14. The test strip 14 can be a reagent test paper. In this case, each test strip 14 includes multiple test media, such as a chemical test pad (CTP) 22, which contains a color-changing reagent for identifying the concentration of certain analytes in patient fluids such as urine, blood, or saliva. The user exposes the instrument 10 to the fluid sample by dipping the diagnostic instrument 10 including the test strip 14 into the patient fluid sample to submerge the test strip 14. As shown in FIG1 , more than one test strip 14 can be adhered to the paddle 12, thereby increasing the number of testable analytes. In certain embodiments, the paddle 12 allows for simultaneous testing of several analytes.

The diagnostic instrument 10, which allows users to test a single fluid sample for multiple patient conditions, is designed to reduce user anxiety and boost confidence for individuals without medical training and limited experience performing medical tests. More specifically, the diagnostic instrument 10 tests for multiple patient conditions, meaning the user does not need to select the appropriate test or determine which conditions are most likely present. Instead, in a single testing session, the user tests for multiple conditions using a single fluid sample exposed to a single diagnostic instrument 10. Furthermore, the diagnostic instrument 10 includes a paddle 12 and a handle 16, making it easy for the user to manipulate the instrument 10. Similarly, the handle 16 ensures that the user is protected from contact with the fluid sample during testing. Thus, users can confidently perform tests using the diagnostic instrument 10 without worrying about accidentally contacting patient fluids. Furthermore, the diagnostic instrument 10 is designed to include clear and easy-to-understand instructions for performing tests and interpreting results, ensuring that untrained users receive accurate diagnostic information from the tests they perform.

Continuing with FIG1 , the diagnostic instrument further includes a color reference, such as a reference color bar (RCB) 28, disposed on the diagnostic instrument 10. The RCB 28 includes a plurality of color samples 29 arranged linearly side by side. For example, the RCB 28 may include color samples 29 for one or more of the following colors: cyan, magenta, yellow, primary color (black), gray, white, red, green, and blue. The color samples 29 correspond to a common color space, such as red-green-blue or cyan-magenta-yellow-primary color (black). The RCB 28 is used for image processing, specifically, to calibrate digital images used by the diagnostic instrument 10 to improve the quality and accuracy of color analysis.

In certain preferred and non-limiting embodiments, the diagnostic instrument 10 further includes an identification mark, such as a unique identification (UID) 24. The UID can be a visual mark that serves as a sign of a specific area of the diagnostic instrument for identification. In addition, the UID 24 can be configured to contain certain identification information about the diagnostic instrument 10, such as a list of the analytes tested, the expiration date of the instrument 10, the conditions tested, and other identification information. The information can be directly printed on the UID 24 or encrypted with the UID 24, such as with a mark or a two-dimensional barcode (such as a QR code). Alternatively, the UID 24 can be associated with information stored elsewhere, such as with a barcode or other near-field communication code. The identification information can be used for a verification process to ensure that the diagnostic instrument 10 is suitable for the test performed and to ensure that it is safe to use, in good working condition, or to solve other problems that may affect the quality and reliability of the test results. It should be noted that the method for automatically analyzing the test strip in the prior art does not include these steps for verifying the diagnostic instrument.

As will be described in greater detail below, the diagnostic instrument 10 is configured so that a digital image of the instrument can be captured using a portable electronic device, such as a smartphone. The diagnostic instrument 10 of the present invention is easier to use than prior art diagnostic instruments, such as the test strips disclosed in the '652 publication. Specifically, unlike previously known systems and methods, the user does not need to hold a test strip contaminated with a biological sample, such as urine, blood, or stool, because the diagnostic instrument does not need to be placed alongside an interpretation chart, such as a Manufacturer's Interpretation Color Chart (MICC), when acquiring a digital image. Furthermore, because the diagnostic instrument 10 does not need to be placed immediately adjacent to a corresponding MICC, there is no possibility of using the wrong MICC for a particular diagnostic instrument (e.g., reading a strip from Manufacturer A with a MICC from Manufacturer B).

Having described the structure of an embodiment of the diagnostic instrument 10 , the system 100 for reading diagnostic test results using the diagnostic instrument 10 will now be described.

With reference to Figure 2, the system 100 for reading diagnostic test results includes a diagnostic instrument 10 and a portable electronic device 110. Generally and in various preferred and non-limiting embodiments, the system 100 is used to obtain, evaluate, analyze, process and/or present image data of the diagnostic instrument 10 obtained by the portable electronic device 110. The system 100 can be used for any type of medical analysis/diagnosis environment, including in a medical clinic, an off-site laboratory without medical supervision, or for home use. It should be understood that different aspects of the present invention can be understood individually, collectively, or in combination with each other. In addition, the image data can include any type or form of visual, video, and/or observable data, including but not limited to discrete images, sequences of images, one or more images from a video, video sequences, and the like.

The portable electronic device 110 may be any type of smartphone (e.g., Apple iPhone, Blackberry), handheld computer (e.g., Apple iPad), or any type of personal computer, network computer, workstation, minicomputer, mainframe, or the like, running any operating system (e.g., any version of Android, Linux, Windows, Windows, Windows NT, Windows 2000, Windows XP, MacOS, UNIX, Solaris, or iOS).

In certain non-limiting embodiments, the portable electronic device 110 includes a camera sensor 112 for obtaining digital images of diagnostic instruments. Currently, several sensor array chips with varying characteristics are available, with CCD (charge-coupled device) and CMOS (complementary metal oxide semiconductor) representing the most common camera sensor chips. Each chip technology offers advantages, and these technologies evolve relatively as designs improve. In summary, CCDs offer larger energy capture fractions and serial readout with minimal local processing, while CMOS offers addressability and processing power for each pixel, but with some loss of sensitivity. The portable electronic device 110 may further include a flash 114 for improving the quality and readability of images captured by the camera sensor 112.

Hereinafter, system 100 is described in terms of functional components and various processing steps. It should be noted that the functional blocks can be implemented by any number of hardware and/or software components configured to perform the specified functions. In a preferred and non-limiting embodiment, the functional components and processing steps are associated with and/or performed using portable electronic device 110. For example, the present invention may use various integrated circuit components (e.g., memory elements, processing elements, logic elements, lookup tables, and the like) that can perform a variety of functions under the control of one or more processors or other control devices. Similarly, the software components of the present invention can be implemented in any programming or scripting language, such as C, C#, C++, Java, assembly language, Extensible Markup Language (XML), or Extensible Stylesheet Transformation (XSLT). Various algorithms can be implemented using any combination of data structures, objects, procedures, routines, or other programming elements.

2 , in one non-limiting embodiment, it is contemplated that functional components and processing steps will be included and/or performed using a portable electronic device 110. In this case, the portable electronic device 110 includes a processor 116 configured to execute program instructions stored on a computer-readable medium 118 associated with the portable electronic device 110. For the purposes of the present discussion, the computer-readable medium 118 may include computer storage media, such as media implemented in any method or technology for storage of information, such as computer-readable instructions, data structures, program modules, or other data, random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, or other memory technology, CD-ROMs, digital versatile disks (DVDs) or other optical disk storage devices, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed by an electronic device, such as the portable electronic device 110.

In certain non-limiting embodiments of the program, processor 116 controls a digital image analyzer 120 for identifying regions of the digital image containing relevant data, color-correcting the digital image, and comparing the corrected portions of the digital image to entries in the MICC to determine test results. Processor 116 may further control a reference tag reader 122 configured to identify and extract information from a UID 24 attached to or associated with the diagnostic instrument 10. Processor 116 may further control a display 122 connected to or associated with the portable electronic device 110 for presenting information (e.g., instructions) for using the diagnostic instrument and test results to a user. Processor 116 may also control a timer 124 for measuring the time between exposure of the diagnostic instrument 10 to a fluid sample and the capture of a digital image of the diagnostic instrument 10. Additionally, in certain embodiments, processor 116 controls a data input device 126 that allows a user to enter additional information, including patient history information, symptoms, and physical characteristics of the user. The data input device 126 may include any input device or user interface known in the art that allows a user to control an electronic device, including but not limited to gestures on a touch screen or any other action that causes a change in readings obtained from a sensor, keypad presses, and the like.

In addition to storing programs for controlling the functions of the portable electronic device 110, the computer-readable medium 118 may also store data including multiple MICC tables used to determine test results. The computer-readable medium 118 may also store raw images obtained by the camera sensor 112, decision trees for determining the patient's condition, and other input data required to execute the functions of the program. In addition, the computer-readable medium 118 may include communication media, such as computer-readable instructions, data structures, program modules, or other data in other transport mechanisms, and include any information delivery media, wired media (such as wired networks and direct wired connections), and wireless media. Computer-readable media may include all machine-readable media, but excludes temporary propagation signals. Of course, any combination of the above items should also be included within the scope of computer-readable media.

In addition, it should be recognized that some or all of the functions, aspects, features, and examples of the present invention can be implemented on a variety of computing devices and systems, wherein these computing devices include appropriate processing mechanisms and computer-readable media for storing and executing computer-readable instructions (such as program instructions, codes, and the like). Functional aspects of applications or other software for directing the functions of portable electronic devices will be discussed in more detail below in conjunction with methods for identifying patient conditions using diagnostic instruments and methods for image processing digital images of diagnostic instruments.

In another non-limiting embodiment, the system 100 includes a data transmitter 128 for transmitting data and information from the portable electronic device 110 to an external electronic device, a computer network, and/or a digital storage device (collectively referred to as a network environment 130, broadly referred to as the "cloud"). Once the data is provided to the network environment 130, the data is made available to interested third parties 132, including caregivers, physicians, third-party payer organizations, insurance and health maintenance organizations, pharmacists, or public health organizations.

Having described the diagnostic instrument 10 and a system including the diagnostic instrument 10 and the portable electronic device 110 , methods for using the diagnostic instrument and obtaining test results will now be discussed in further detail.

Initially, as depicted in Figure 3. A method for obtaining a digital image of a diagnostic instrument is described. The user begins by installing a software program configured to acquire and analyze the digital image of the diagnostic instrument on a portable electronic device. Once the software program is installed, the user initiates the program 210 by means of an active activation component (e.g., pressing a "start" button on the display screen of the portable electronic device). The user then exposes the diagnostic instrument 212 to the biological sample, which exposes a plurality of CTPs to the analytes contained in the sample and initiates a chemical reaction between the CTPs and the analytes. In certain embodiments, a timer is started when the diagnostic instrument is exposed to the sample. After a predetermined time has passed, the portable electronic device prompts the user to capture a digital image of the diagnostic instrument. The time point at which the digital image is captured is critical because the color of the CTPs continues to change over time. Therefore, the absence of this acquisition window may invalidate any test results from the diagnostic instrument. Alternatively, additional calculations may be performed to compensate for incorrect exposure times.

The user captures 214 a digital image of the diagnostic instrument 10 using a camera sensor of a portable electronic device. In some embodiments, the portable electronic device may provide instructions for obtaining the digital image, such as by suggesting a preferred camera position or lighting environment. For example, in some embodiments, when preparing to capture a digital image of the diagnostic instrument, the user interface superimposes a virtual outline of the diagnostic instrument onto a real image acquired by the camera sensor in video mode. The user is then instructed to overlap the virtual outline with the image of the diagnostic instrument and to accurately capture the picture as indicated by a timer. When the user triggers the camera shutter, the camera is configured to switch from video to high-resolution mode to capture a high-resolution single-frame image of the diagnostic instrument. The captured digital image includes at least a portion of the RCB, CTP, and/or UID of the diagnostic instrument. More specifically, it is preferred to capture a high-definition image of the diagnostic instrument under a flash or other standardized lighting conditions (if available) to provide the most reproducible lighting conditions.

In certain non-limiting embodiments and with reference to FIG4 , once a digital image of the diagnostic instrument is obtained, the portable electronic device may be used to verify 216 the diagnostic instrument. Specifically, an optical reader (e.g., a barcode, matrix barcode reader, two-dimensional barcode reader, or QR code reader) associated with the portable electronic device is used to scan the captured digital image to locate the UID. The UID includes or corresponds to information about the diagnostic instrument being tested. Software is configured to ensure that the diagnostic instrument is safe to use and suitable for a particular application based on the identification information from the UID. Additionally, the UID verification step may include using the identification information from the UID to select the correct MICC from available options stored on the portable electronic device for use in analyzing the results of the tested diagnostic instrument.

After the verification step 216, a geometric correction is performed 218 to determine the position of other elements of the diagnostic instrument (i.e., the RCB and CTP) based on the position and orientation of the UID. The geometric correction compensates for a wide range of user positioning and posture errors that may occur due to the user holding the instrument to capture the digital image. A geographic correction can be defined based on the pitch, roll, and yaw angles of the diagnostic instrument in the digital image. Based on the geometric correction, the position of the RCB and CTP can be effectively identified. The method further includes applying a local image correction to the identified portion of the digital image that includes the RCB or CTP, for example, analyzing the digital image to surround the boundaries of each identified region and applying a spatial guard band only within it.

Continuing with reference to FIG4 , after obtaining the digital image and performing geometric correction, processing the digital image to remove image noise and correct image coloring is performed 220. It should be noted that all operations, corrections, calculations, and modifications are performed on a stored copy of the high-definition image. In this way, the original image remains separate and can be used for later analysis if necessary. More specifically, the color correction process corrects the color of the portion of the captured image copy that includes the CTP based on calibration measurements and correction offsets determined from analysis of the portion of the digital image that includes the RCB.

Once the portion of the digital image containing the CTP has been color corrected, the corrected color 222 can be compared with the color samples from the MICC. As described in more detail below, the comparison between the CTP color change and the MICC is based on an interpolation process. The MICC is a table depicting multiple possible results (e.g., color samples) for one or more of the CTPs on a diagnostic instrument. An exemplary MICC 150 suitable for a standard test strip is depicted in FIG5 . The MICC 150 includes multiple color samples 152 corresponding to a range of possible color changes for the tested CTP. Each color sample corresponds to a CTP color change over a range of analyte concentrations or titrations (e.g., absent, normal, positive, strongly positive ...). The MICC 150 is typically provided by the manufacturer of the tested test strip. Continuing with reference to FIG4 , based on the comparison between the corrected CTP color and the MICC color samples, a test result (e.g., concentration or titration) is determined 224.

In certain embodiments, a predetermined MICC value is also used to provide confirmation that the diagnostic instrument is providing valid results and is suitable for use. More specifically, the MICC represents the range of possible color variations for the CTP. If the color of the identified area does not correspond to a possible test result color, it is assumed that an incorrect MICC was used to analyze the test result or that the diagnostic instrument is defective. Therefore, any results that fall outside the color range defined by the MICC are discarded.

Continuing with reference to FIG4 , the test results of individual CTPs can be interpreted 226 individually or in combination with other test results and diagnostic information to determine a patient condition 226. For example, multiple test results indicating the presence or absence of several different analytes in a fluid sample can be considered in combination to determine a possible patient condition. Similarly, if the test results suggest several possible patient conditions, the method can further include asking the patient various diagnostic questions to eliminate certain possible conditions to arrive at the most likely patient condition. In certain embodiments, the test results and/or patient condition information are presented to the user on a visual display of a portable electronic device.

Having generally described methods for using a diagnostic instrument, capturing digital images of the diagnostic instrument, and determining test results using a portable electronic device, various processes, algorithms, and methods for analyzing digital images will now be described in greater detail. It should be understood that the processes described below are intended merely to be exemplary processes and methods for analyzing digital images of a diagnostic instrument and are not intended to limit the scope of the present invention in any way. Furthermore, it should be understood that the described processes can be implemented using portable electronic devices or other computers and processing equipment known in the art that are within the scope of the present invention.

UID-based verification of diagnostic instruments

As shown in FIG4 , a non-limiting embodiment of the method includes a step of verifying 216 the UID to ensure that the diagnostic instrument is suitable for the test being performed. The verification step requires determining the position of the UID on the digital image of the diagnostic instrument. To determine the UID position, the digital image can be scanned using a digital reader or similar image processing algorithm or device. The scanning function can also be used to ensure that the entire diagnostic instrument is acceptably in focus in the digital image. If the digital image is not properly focused, the user can be prompted to obtain an alternative image of the diagnostic instrument.

UID can be implemented as a matrix or two-dimensional bar code, such as a QR code. In other embodiments, the UID is a bar code or a near-field communication tag. The UID includes or is associated with some identification information about the diagnostic instrument, and the identification information includes the manufacturing date of the diagnostic instrument, the expiration date of the diagnostic instrument, the analyte tested by the instrument, identification information about the test subject, or patient condition information. For QR codes and similar visual marks, the identification information is clearly embedded in the UID itself. The embedded information can be encrypted using various encryption security mechanisms as known in the art. Alternatively, the information on the UID can point an electronic device or a digital reader to the information stored on an external device. The UID is read according to a standard algorithm known in the art. Optionally, the information about the diagnostic instrument contained on the UID can be used to compare the diagnostic instrument with other available test instruments to ensure that the software and hardware of the diagnostic instrument and the portable electronic device are compatible and are the most suitable test devices that can be used for a given application.

Additionally, verification operations 216 can be used to ensure that the device was legitimately obtained and has not been tampered with during shipment to the user. For example, the UID may contain information about the manufacturer, origin, and traceability of the diagnostic instrument (e.g., the diagnostic instrument's point of origin and any third parties that have handled the instrument since its manufacture). If any identifying information is suspicious or incorrect, the diagnostic instrument may be rejected and the user informed that the diagnostic test cannot be performed. Such verification actions prevent the use of fraudulent and/or unsafe products, such as those sold illegally or obtained from unauthorized third parties.

Perform geometric correction to identify CTP and RCB

The method further includes performing geometric correction 218 on the digital image to find the appropriate CTP and RCB sub-images of the CTP and RCB taking into account the geometric deformation of the original image. The process takes into account the geometric deformation of the original image to find the appropriate CTP and RCB sub-images, which are then cropped as accurately as possible to remove any edge artifacts from the identified areas of the digital image, leaving only the individual colored areas of the CTP and RCB for further analysis.

When it's time to take a picture, the user interface superimposes a virtual outline of the paddle onto the real image captured by the camera in video mode, followed by a single frame captured in high-resolution camera mode. In this embodiment, the user is instructed to overlay the virtual outline with the image of the paddle and take the picture precisely as the timer indicates.

When the user triggers the camera shutter, the camera switches from video to high-resolution mode to capture the best possible image of the paddle, thereby improving the accuracy of the method described in this patent application.

Specifically, geometric correction is based on the position of the UID in the digital image. Initially, the position of the UID is identified by scanning the digital image, as described above in conjunction with the verification process. Referring to Figures 6A to 6D, in certain embodiments of the method, four UID 24 points A, B, C, and D are identified on the corners of the UID 24 to form a square of known size that encloses the UID 24. Based on the orientation of the UID 24 in the digital image, the vertical (X-scaling) and horizontal (Y-scaling) scaling of the diagnostic instrument 10 and the scaling factor are calculated, including the yaw angle, pitch angle, and roll. Based on the calculated position and scaling factor of the UID 24, the theoretical position of the CTP 22 and RCB 28 can be calculated. The calculated theoretical position is identified on the digital image. The identification of the CTP and RCB allows the CTP and RCB sub-images to be extracted from the digital image of the diagnostic instrument 10. The calculations required to determine the theoretical position are described herein. The symbols used in the following formula are:

A(x,y)＝Ax,Ay

Ti(x,y)＝Tix,Tiy

Referring to Figure 6B, the yaw angle (rotation about the Z axis) is measured directly using the following equation:

Yaw angle = atan((Ay-Dy)/(Ax-Dx))

And the position is corrected through rotation about point A, resulting in new reference values X' and Y'.

6C , the pitch angle (rotation about the Y axis) is approximated by the difference in length between the projections of AB and DC on the Y′ axis.

Pitch angle approximation = abs(Dy-Cy)/abs(Ay-By)

Pitch correction = (abs(Dy-Cy)/abs(Ay-By))^3,

Referring to FIG6D , the roll angle (rotation around the X axis) is approximated by the axis Y′ and the AB or DC line segment.

DC angle=atan((Cx-Dx)/(Cy-Dy));

The composite correction for both roll and yaw is calculated as:

AngFact = sin(DC angle) + sin(yaw angle);

The coordinates of CTP 22 are calculated by applying the following corrections to the points T1 ..Tn defined in FIG. 6A to obtain its transformation TA.

TAy=round(Tiy*Yscale);

TAx=round(Tix*Xscale-AngFact*TAy);

The coordinates of the RCB 28 can be calculated using the same equation, thereby providing a theoretical location of the RCB 28 on the digital image.

CTP noise removal and CTP color correction

Continuing with reference to FIG4 , the CTP image identified through geometric calculations may be imperfect for various reasons. Therefore, once the CTP and RCB sub-images are identified and extracted through geometric correction, processing is performed to remove CTP noise and correct the color of the digital image 220 to accurately reflect the coloring under standard lighting conditions. However, it should be understood that the calculated theoretical positions of the CTP and RCB, and the resulting extracted sub-images, may be inaccurate and not fully aligned with the RCP and CTP for a variety of reasons. Referring to FIG7A through FIG7C , a background artifact 312 from the housing of the diagnostic instrument 10 may be incorrectly included within the CTP sub-image 310 identified through geometric correction calculations described above. Background artifact 312 is adjacent to or surrounds the actual CTP image 314. As shown in FIG7A , background artifact 312 is present to the left and top of CTP sub-image 310. FIG7B largely includes background artifact 312 at the top and a second background artifact 316 to the right of the actual CTP image 314. FIG7C includes a small edge background artifact 312 surrounding the actual CTP area 314. Background artifacts 312, 316 can be removed by applying local image correction, in which a spatial guard band is placed around the boundaries of the actual CTP image 314 and only within those boundaries. Background artifacts 312, 314 outside the area enclosed by the guard band are removed from the CTP sub-image. The more uniform color patch within the guard band (e.g., the actual CTP image 314) is then filtered and optimized to improve image quality.

8 , due to the length and tilt of the RCB sub-image 318 extracted from the digital image of the diagnostic instrument 10, the RCB 28 is also often not accurately identified by the geometric correction calculation. For example, the RCB sub-image 318 may include noisy background lines 320 at the top and bottom of the actual RCB image 322, as shown in FIG8 . Therefore, an additional step is required to remove the background lines 320 from the sub-image 318 in order to accurately identify the RCB 28. This operation is performed by applying a variance operator to the RCB sub-image 318 line by line. Longitudinal lines with low variance that cross the RCB sub-image 318 are not part of the RCB 28 and can be deleted. However, lines that extend across the actual RCB image 322 will have a high and well-known variance. Therefore, such high-variance lines are not filtered out and are not used to capture the actual RCB image 322.

Additional image defects, including noise from the camera sensor, artifacts caused by changing lighting conditions, imperfections in the sample itself, variations in CTP chemistry, or any combination thereof, may also be present in the actual CTP and RCB images 314, 322, even after removing background artifacts 312, 316 and background lines 320. These defects can be removed through filtering and color correction. However, the challenge of filtering noise in medical applications is to avoid tampering with the original data. This is particularly true in color spaces, where classical signal processing methods such as linear filtering can smear or distort the sample and produce problematic results. For example, a single red pixel averaged over a white area introduces a low level of pink that can be misinterpreted as a test result. Nitrate CTP is a good example, where even the slightest detection of pink corresponds to a positive result. Therefore, the filtering method of the present invention is based on a sorting operation that does not modify the original data and does not introduce color into existing points, even at a minimal level. Furthermore, the quality of the identified CTP areas is further improved by conditionally rejecting anomalous color points that fall far outside the nominally uniform color across the test panel. Such conditional rejection of outliers provides a significant improvement in reducing error without changing the original data.

In light of these challenges, in one embodiment, a median filter (e.g., a median filter developed by MathWorks for use with MATLAB data analysis software) can be applied to the actual CTP and RCB images 314, 320 after background artifacts are removed. The median filter has the advantages of reducing contamination of the CTP and RCB images by boundary points that have not been rejected by the guard bands and providing an excellent solution for optimal values without modifying the original data. Applying the median filter to the actual CTP and RCB images (e.g., camera-captured CTP and RCB images) provides explicit camera-captured CTP colors and explicit camera-captured RCB colors. More specifically, the median filter is applied in the line direction and then in the column direction.

Due to the potential variations in lighting conditions when capturing digital images, camera-captured CTP colors must be color corrected before comparison with the MICC to calibrate the digital image to the MICC color space. It should be noted that because the diagnostic instrument's digital images capture both the RCB and CTP under the same lighting conditions, the RCB digital image reflects the same noise and bias conditions as the CTP. Therefore, the present invention recognizes that the RCB can serve as a calibration reference to color correct the color-averaged CTP values.

In one embodiment, color correction values are determined by identifying a white sample of the RCB. Color correction factors are determined by identifying any colors other than white present in the camera-captured white sample of the RCB. The correction factors are applied to the camera-captured CTP colors using a white balance algorithm as known in the art. For example, Jeny Rajan's white balance algorithm for MATLAB (available at https://sites.google.com/site/jenyrajan/) can be used in conjunction with the present invention. The white balance algorithm is effective for color correction of red, green, and blue images, such as digital images from diagnostic instruments.

Alternatively, and in a preferred and non-limiting embodiment, the color correction algorithm uses additional reference samples from the RCB to calculate both black and white correction factors and color correction factors for the digital image. As an inherent property of the invented method, the colors of each of the squares in the RCB (cyan, magenta, yellow, primary (black), gray, white, red, green, and blue) are known under standard lighting conditions (e.g., D65). The color values of the RCB under standard lighting conditions are referred to as reference RCB (RefRCB) values. These known standard color values are compared with values obtained from the actual RCB image 322, referred to as the camera-captured RCB (CCRCB), acquired according to the process described above. With two data sets, CCRCB and RefRCB, it is possible to construct an inverse matrix that transforms the CCRCB into the RefRCB. Examples of solutions for deriving the inverse matrix and for correcting the color of the CTP based on the derived inverse matrix include the following:

1. Correct the image by adjusting the brightness of the square by a factor of γ

2.L _out = AL _out ^gamma

3. This is for B&W brightness, which means batch correction

4. Use another γ factor to balance the RGB deviation of the three colors

5.a _out =Ba _out ^gamma1

6. This is used for color adjustment, usually a and b and Lab

7.CMY values are used for verification

Once the gamma factors (A, γ, B, γ1) are derived, corrections are applied to the explicit camera-captured CTP colors to bring the CTP colors into the MICC color space.

A schematic representation of the color correction process described above is depicted in FIG9 . As shown in FIG9 , a digital image of the diagnostic instrument 10, including the CTP 22 and RCB 28, is acquired using a camera 410 of a portable electronic device under various real-world, known or unknown lighting conditions. This image is referred to as the CCRCB. A spectrophotometer 412 is used to compare the digital image of the RCB 28 with the known color values of the RCB 28 acquired under standard or ideal lighting conditions. This image is referred to as the RefRCB. The comparison between the CCRCB and the RefRCB is used to create an inverse matrix 414 for mapping the CCRCB onto the RefRCB. The inverse matrix 414 is applied to the camera-captured CTP colors to transform them into colors in the same color space as the MICC 416. Once the CTP is transformed to obtain color-corrected CTP colors 418, the color-corrected CTP can be compared to the MICC, as both colors exist in the same color space. In this way, the digital image of the diagnostic instrument is effectively calibrated using the MICC 416, even when the digital image is acquired under real-world or unknown lighting conditions.

Comparison of CTP and its corresponding MICC

As previously described, MICCs for several different types of CTP arrangements can be stored on a computer-readable medium contained on or associated with a portable electronic device. When the method described in the present invention verifies the UID in Figure 4, it also selects an appropriate MICC to interpret the paddle. More specifically, the verification process uses the identification information contained on the UID of the tested diagnostic instrument to select the correct MICC to interpret the results of a specific test. The verification process effectively prevents users from using the wrong diagnostic instrument or an incorrect MICC, even when several families of diagnostic instrument products have similar appearances or CTP arrangements. The color of the color-corrected CTP is compared with the color value from the corresponding MICC to determine the analyte concentration of the sample solution. The measured color is compared with the MICC value by an interpolation process.

Interpolation of test results using the MICC can be performed in at least two ways. Referring to Figures 10 and 11, the first and simplest method used in imaging processes used in the prior art is to evaluate the distance in color space between the color-corrected CTP color and the MICC value. Schematic diagrams depicting such interpolation are depicted in Figures 10 and 11. As shown in Figure 10, the MICC 416 for a particular CTP (e.g., a set of 318 color values representing color changes for various analyte concentrations) is represented in RGB color space 420 as a series of discrete points 422 corresponding to the MICC 416 color sample. As shown in Figure 10, the discrete points 422 are connected by solid trajectory lines 424. Referring to Figure 11, the color-corrected CTP color 426 is also included in the color space 420. The method calculates the distance D between the color-corrected CTP color 426 and each of the discrete points 422. The closest discrete point 422 is thereby identified. The test result for the CTP color is reported as the analyte concentration of the closest discrete point.

Referring to Figures 12A and 12B , a second preferred method incorporates an additional metric by using the shortest distance dh between the color-corrected CTP color 426 and the interpolated color trajectory 428 derived from the discrete points 422. This distance dh can be used in two simultaneous ways. First, a color trajectory function can be derived by applying polynomial interpolation. The predicted concentration is calculated using the shortest perpendicular distance dh between the color-corrected CTP color 426 and the interpolated color trajectory 428. Second, if the length dh perpendicular to the interpolated color trajectory 428 is greater than a predetermined value, the measurement is rejected as suspicious. Conversely, if dh is less than a given predetermined value, the measurement can be deemed trustworthy. Furthermore, known algorithms can be used to further refine the concentration by proportionally interpolating between the two nearest discrete points 422 to the color-corrected CTP 426 to further improve quantitative accuracy. In an alternative embodiment, the perpendicular distance dc between the color-corrected CTP color 426 and the locus line 424 connecting the discrete points 422 (defined as the chord between the discrete points 420) also yields a valuable and simplified method for calculating density that improves upon currently available methods.

In either case, the color-corrected portion of the digital image, including the CTP, is proportionally mapped onto an accurately interpolated polynomial or chordal fit in a selected color space, such as a red-green-blue (RGB) color space. While the above discussion refers to an RGB color space, those skilled in the art will appreciate that any color space (e.g., CMYK, CIE, spot colors, Munsell, etc.) may be used.

Advantageously, the above method is very tolerant to nonlinearities and does not require any integral relationship to any characteristics of human vision, making its value and interpretation independent of the observer's color vision, the ambient lighting when the digital image was taken, residual segmentation, or in practice the most commonly encountered errors (for which no previous calibration and compensation have been made).

Once multiple analyte concentrations are calculated, the test results can be provided to the user. Additionally, a complete set of test results can be combined to interpret a medically relevant set to more specifically determine the patient's condition.

Test results and titration of CTP

The test results are presented to the user via a visual display connected to or associated with the portable electronic device. A simple way to visualize the test results is to present them to the user using an image of the MICC and drawing a border around the nearest MICC color sample. A possible visual depiction of the MICC 416 showing the selected color sample 430 corresponding to the identified test result is shown in FIG13 .

Another way to visualize the test results is to print the analyte tested and the concentration or titration (e.g., normal, positive, strong positive, etc.) in a list or table. The list or table can be presented on the visual display of the device, as shown below in Table 1. The correspondence between these titrations and the colors read by the algorithm is encoded in a lookup table that links the MICC to the titration. Typical values provided are negative, trace, small (+), medium (++), and large (+++).

Table 1

White blood cells medium

Nitrite negative

Urobilinogen 1...

Interpretation of the results

The test results can be further analyzed to provide the user with information about possible patient conditions. In a simple form, the explanation can include displaying additional facts about the patient's condition and possible treatment options. In further embodiments, the method can consider the results of two or more separate tests to provide additional information about the patient's condition. For example, an indication that a patient has both high white blood cell levels and high nitrites suggests a urinary tract infection (UTI).

In cases where this explanation may lead to ambiguity, the software can participate in the user dialogue by asking the user additional contextual questions to resolve ambiguity and provide a general explanation based on the latest medical technology. These additional questions are often implemented as decision trees, a method well known in the art. For example, if the diagnostic instrument 10 identifies high levels of bilirubin, the software's decision tree function can ask the user for additional information about the medications they are taking to detect whether the user is experiencing an allergic reaction to a specific medication. Exemplary decision trees suitable for the diagnostic instrument of the present invention are depicted in Figures 14 and 15.

Security embodiment for validating unused diagnostic instruments

In another non-limiting embodiment of the invented method, a diagnostic instrument may be inspected prior to use to ensure it is undamaged and fit for use. More specifically, storage, conditioning, transportation, and exposure of the diagnostic instrument to contaminants such as air can damage the instrument, rendering it unreliable during use. It should be noted that exposure to contaminants may render a diagnostic instrument unfit for use even if the instrument has not yet reached its expected expiration date. Therefore, steps are needed to ensure that the diagnostic instrument is capable of producing accurate results.

As shown in the exemplary embodiment of FIG. 16 , in this embodiment, the user captures an image of the diagnostic instrument before exposing it to a biological sample 228. The remaining steps are equivalent to the method for capturing digital images depicted in FIG. The step of capturing an image of the unexposed diagnostic instrument before exposing it to a fluid sample serves to verify that the initial (e.g., unused) color of the CTP before contact with the fluid sample is within a normal range. More specifically, the appearance of the unused CTP is compared to the expected original value using the color comparison algorithm described above in conjunction with comparing the color-corrected CTP color to the MICC. However, rather than comparing the color-corrected CTP color to the MICC, the color-corrected CTP values are compared to a safety table established during the risk and quality management process for the diagnostic instrument. An exemplary safety table 432 is depicted in FIG. Table 432 includes the smallest possible subset 434 of colors for each unused CTP. If the color-corrected CTP color for an unused CTP differs from the color sample in table 432 by more than a predetermined amount, the diagnostic instrument is rejected as defective. More specifically, the safety table defines the tolerances for acceptable, unexposed diagnostic instrument colors. Any deviation from the expected tolerances is rejected. It should also be noted that Table 432 reflects colorimetric values for dry samples, which may appear lighter in color than the wet values processed with exposed samples and reported in the MICC.

Similarly, after exposing the diagnostic instrument to a fluid sample and before performing additional image analysis on the diagnostic instrument, the digital image of the diagnostic instrument can be compared to a set of colors corresponding to the maximum possible CTP color change 436. The method for comparing the CTP color change to the maximum color change value is the same as the comparison process described above. If the CTP color change is found to exceed the theoretical maximum possible color change, the result is rejected as invalid. In this case, no further image processing is required, and the diagnostic instrument should be discarded as defective.

The above methods can be implemented on a variety of electronic and computing devices and systems, including portable electronic devices and/or server computers, wherein these computing devices include appropriate processing mechanisms and computer-readable media for storing and executing computer-readable instructions (e.g., program instructions, code, and the like). As shown in FIG. 18 , a personal computer 1900, 1944 is provided in a computing system environment 1902. This computing system environment 1902 may include, but is not limited to, at least one computer 1900 having certain components for appropriately operating, executing code, and generating and communicating data. For example, the computer 1900 includes a processing unit 1904 (commonly referred to as a central processing unit or CPU) for executing computer-based instructions received in an appropriate data form and format. Additionally, this processing unit 1904 may be in the form of multiple processors that execute code in serial, parallel, or any other manner for appropriate implementation of the computer-based instructions.

To facilitate appropriate data communication and information processing between the various components of the computer 1900, a system bus 1906 is utilized. The system bus 1906 can be any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, or an internal bus using any of a variety of bus architectures. In particular, the system bus 1906 facilitates data and information communication between the various components (whether internal or external to the computer 1900) via a variety of interfaces, as discussed below.

The computer 1900 may include a variety of discrete computer-readable media components. For example, such computer-readable media may include any media accessible by the computer 1900, such as volatile media, non-volatile media, removable media, non-removable media, and the like. As another example, such computer-readable media may include computer storage media, such as media implemented in any method or technology for storage of information (e.g., computer-readable instructions, data structures, program modules, or other data), random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, or other memory technology, CD-ROMs, digital versatile disks (DVDs) or other optical disk storage devices, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed by the computer 1900. Additionally, such computer-readable media may include communication media, such as computer-readable instructions, data structures, program modules, or other data in other transport mechanisms, and include any information delivery media, wired media (e.g., wired networks and direct-wired connections), and wireless media. Computer-readable media may include all machine-readable media, excluding only transitory propagation signals. Of course, combinations of any of the above should also be included in the scope of computer-readable media.

The computer 1900 further includes a system memory 1908 having computer storage media in the form of volatile and nonvolatile memory, such as ROM and RAM. A basic input/output system (BIOS) with appropriate computer-based routines assists in transferring information between components within the computer 1900 and typically stored in ROM. The RAM portion of the system memory 1908 typically contains data and program modules that are immediately accessible to or currently being operated on by the processing unit 1904, such as an operating system, application programming interfaces, applications, program modules, program data, and other instruction-based computer-readable code.

18 , the computer 1900 may also include other removable or non-removable, volatile or non-volatile computer storage media products. For example, the computer 1900 may include a non-removable memory interface 1910 that communicates with and controls a hard disk drive 1912 (i.e., a non-removable, non-volatile magnetic medium); a removable non-volatile memory interface 1914 that communicates with and controls a magnetic disk drive unit 1916 that reads from and writes to a removable non-volatile magnetic disk 1918; an optical disk drive unit 1920 that reads from and writes to a removable non-volatile optical disk 1922 (e.g., a CD ROM); a universal serial bus (USB) port 1921 for connecting to a removable memory card; and the like. However, it is contemplated that other removable or non-removable, volatile or nonvolatile computer storage media may be used in the exemplary computing system environment 1900, including but not limited to magnetic cassettes, DVDs, digital video tape, solid-state RAM, solid-state ROM, etc. These various removable or non-removable, volatile or nonvolatile magnetic media communicate with the processing unit 1904 and other components of the computer 1900 via the system bus 1906. The drives and their associated computer storage media discussed above and illustrated in FIG18 provide storage for the operating system, computer-readable instructions, applications, data structures, program modules, program data, and other instruction-based computer-readable code for the computer 1900, whether or not this information and data is duplicated in the system memory 1908.

A user may enter commands, information, and data into the computer 1900 through some attachable or operable input device, such as a keyboard 1924, a mouse 1926, or the like, via a user input interface 1928. Of course, a variety of such input devices may be utilized, such as a microphone, a trackball, a joystick, a touch pad, a touch screen, a scanner, and the like, including any arrangement that facilitates the entry of data and information from an external source into the computer 1900. As discussed, these and other input devices are often connected to the processing unit 1904 via a user input interface 1928 that is coupled to the system bus 1906, but may be connected through other interface and bus structures, such as a parallel port, a game port, or a universal serial bus (USB). Still further, data and information may be presented or provided to the user in an understandable form or format through some output device, such as a monitor 1930 (to physically display such information and data in electronic form), a printer 1932 (to physically display such information and data in printed form), a speaker 1934 (to audibly present such information and data in audible form), and the like. All of these devices communicate with the computer 1900 via an output interface 1936 coupled to the system bus 1906. It is contemplated that any such peripheral output devices may be used to provide information and data to a user.

The computer 1900 can operate in a network environment 1938 through the use of a communication device 1940 that is integrated into the computer or remote from the computer. This communication device 1940 can be operated by and communicate with the other components of the computer 1900 via a communication interface 1942. Using such an arrangement, the computer 1900 can connect to or otherwise communicate with one or more remote computers, such as a remote computer 1944, which can be a personal computer, server, router, network personal computer, peer device, or other common network node, and typically includes many or all of the components described above in connection with the computer 1900. Using an appropriate communication device 1940, such as a modem, network interface, or adapter, the computer 1900 can operate within and communicate via local area networks (LANs) and wide area networks (WANs), but may also include other networks, such as virtual private networks (VPNs), office networks, enterprise networks, intranets, the Internet, and the like. It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers 1900, 1944 may be used.

As used herein, a computer 1900 includes appropriate specially designed or conventional software or is operable to execute the software to perform and implement the processing steps of the methods and systems of the present invention, thereby forming a dedicated and specific computing system. Thus, the methods and systems of the present invention may include one or more computers 1900 or similar computing devices having a computer-readable storage medium capable of storing computer-readable program code or instructions that cause a processing unit 1902 to execute, configure, or otherwise implement the methods, processes, and transformation data manipulations discussed below in conjunction with the present invention. Still further, the computer 1900 may be in the form of a personal computer, a personal digital assistant, a portable computer, a laptop computer, a palmtop computer, a mobile device, a mobile phone, a server, or any other type of computing device having the necessary processing hardware to appropriately process data to effectively implement the computer-implemented methods and systems of the present invention.

Although the present invention has been described in detail for purposes of illustration based on what are presently considered to be the most practical and preferred embodiments, it should be understood that such details are solely for that purpose and that the invention is not limited to the disclosed embodiments, but rather is intended to cover modifications and equivalent arrangements within the spirit and scope of the appended claims. For example, it should be understood that the present invention contemplates that, to the extent possible, one or more features of any embodiment can be combined with one or more features of any other embodiment.

Claims (49)

1. A computer-implemented method for quantifying color changes of at least one test medium on a diagnostic instrument, the method comprising: The diagnostic instrument, which includes at least one color reference comprising multiple reference samples of different colors and multiple test media each having multiple reagents, captures digital images of at least a portion of the biological sample exposed to the biological sample by a camera sensor. Identify at least one of the plurality of reference samples other than the white reference sample for the at least one test medium used in the diagnostic instrument; Determine the visible camera captured color of the at least one reference sample and the visible camera captured color of the at least one test medium; Color correction is performed on the visible camera-captured color of the at least one test medium based on a correction factor derived at least partially from the visible camera-captured color of the at least one reference sample to determine the corrected test medium color; and The test results are determined by comparing the color of the calibrated test medium with a set of possible test medium colors corresponding to a predetermined analyte concentration to determine the analyte concentration of the biological sample being tested. 2. The computer implementation method according to claim 1, wherein the plurality of test media of the diagnostic instrument are arranged according to a plurality of test-specific sequences. 3. The method of claim 1, wherein the diagnostic instrument further comprises identification information or an identification tag associated with the diagnostic instrument, and wherein the digital image captured by the diagnostic instrument contains at least a portion of the identification tag. 4. The method of claim 3, wherein the identification mark is at least one of the following: a barcode, a QR code, a near-field communication tag, or any combination thereof. 5. The method of claim 3, wherein the identification information comprises at least one of the following: the manufacturing date of the diagnostic instrument; the expiration date of the diagnostic instrument; the analyte used for testing by the diagnostic instrument; identification information about the test subject; patient condition information; or any combination thereof. 6. The method of claim 3, further comprising verifying the diagnostic instrument by analyzing the portion of the digital image containing the identification marker to determine the identification information and by determining, based on the identification information, whether the diagnostic instrument is in use. 7. The method of claim 6, wherein verifying the diagnostic instrument further comprises selecting at least one possible test medium color based on the identification information. 8. The method according to claim 3, wherein the identification step further comprises: Scan the digital image to determine the location of the identification marker on the digital image; The geometric correction for the digital image is determined at least in part based on the position of the identification marker, the geometric correction including a rotation angle of the diagnostic instrument about at least one of the following: the x-axis, y-axis, z-axis, or any combination thereof; and The positions of the at least one reference sample and the at least one test medium on the digital image are calculated, at least in part, based on the position of the identification marker and the geometric correction. 9. The method according to claim 1, wherein the identification step further comprises: Identify the region of the digital image containing the reference sample; and Background artifacts are removed from the identified region by applying a variance operator to remove the low-variance portion of the identified region while maintaining the high-variance portion of the identified region. 10. The method of claim 9, wherein the identification step further comprises: Identify the region of the digital image containing the reference sample and the region of the digital image containing the at least one test medium; Identify edge artifacts on the boundaries of the identified region; and Remove the identified edge artifacts from the digital image. 11. The method of claim 1, wherein the determining step further comprises: A protective zone is defined around the boundary of the reference sample and the at least one test medium, or only within the boundary, to form a closed region; and Color noise within the enclosed region is reduced by averaging the colors within the enclosed region of the reference sample and the at least one test medium. 12. The method of claim 11, wherein a median filter is applied to at least one closed region to determine the explicit camera-captured color of at least one reference sample therein or to determine the explicit camera-captured color of at least one test medium therein. 13. The method of claim 1, further comprising: A white reference sample is identified among multiple reference samples in the digital image, the white reference sample being white under standard lighting conditions; The correction factor is further determined based at least in part on the average color of the white reference sample in the digital image; and The color of the at least one test medium captured by the camera is further corrected by applying the correction factor using a white balance algorithm. 14. The method of claim 1, further comprising: The luminescence of the reference sample is compared with the predetermined expected luminescence to determine the luminescence correction factor; The color captured by the camera on the reference sample is compared with the color of the expected sample to determine the color correction factor; and The camera-captured colors of the at least one test medium are corrected at least in part based on the luminescence correction factor and the color correction factor. 15. The method of claim 1, further comprising rejecting the digital image if the color of the calibrated test medium exceeds a predetermined value. 16. The method of claim 1, wherein the camera-captured reference sample and the camera-captured test medium each comprise a plurality of color components defining at least one color space, and wherein the at least one color space is at least one of the following: red-green-blue RGB; cyan-magenta-yellow-primary color CMYK; International Commission on Illumination (CIE) color space; spot color space; Munsell color space; or any combination thereof. 17. The method of claim 1, wherein the comparison step further comprises: Determine the possible test medium color that is closest to the calibrated test medium color; and Determine the concentration of the analyte corresponding to the closest possible color of the test medium. 18. The method of claim 1, wherein the comparison step further comprises: The possible test media colors are mapped to at least one color space to form at least one color track; Calculate the shortest substantially perpendicular distance between the calibrated test medium color and the at least one color trajectory to determine the intersection point; and The concentration of the analyte in the biological sample is calculated at least in part based on the location of the intersection point. 19. The method of claim 18, wherein the at least one color trajectory is derived by polynomial interpolation of the group of colors. 20. The method of claim 19, further comprising calculating an error probability based on the shortest vertical distance between the color of the calibration test medium and the at least one color trajectory. 21. The method of claim 1, further comprising displaying at least a portion of the test results on a visual display of a portable electronic device. 22. The method of claim 1, further comprising transmitting at least a portion of the test results to an external source, the external source including at least one of: an external computer network, an external data collection device, the Internet, or any combination thereof. 23. The method of claim 1, wherein the capturing step further comprises exposing the diagnostic image to a flash to improve the illumination conditions of the digital image. 24. The method of claim 1, wherein at least one of the following is performed using a portable electronic device: the capture step; the identification step; the determination step; the color correction step; the comparison step; or any combination thereof. 25. The method of claim 24, wherein the portable electronic device is at least one of the following: a smartphone, a tablet PC, a computer, or any combination thereof. 26. A method for validating a diagnostic instrument, comprising: The diagnostic instrument captures at least a portion of a pre-processed digital image of the diagnostic instrument before exposing it to a biological sample. The diagnostic instrument includes at least one color reference comprising multiple reference samples of different colors other than white and multiple test media each containing a reagent that changes color in the presence of a specific analyte in the biological sample. Identify at least one of the plurality of test media in the pre-ready digital image of the diagnostic instrument; Compare the color of the at least one test medium with the colors of a set of possible test media used for reagents that have not yet been exposed to the analyte; and Whether the diagnostic instrument is in use is determined at least in part based on the color of the at least one test medium. 27. The method of claim 26, wherein the diagnostic instrument further includes identification information or an identification tag associated with the diagnostic instrument, and wherein the digital image captured by the diagnostic instrument includes at least a portion of the identification tag. 28. The method of claim 27, wherein the identification mark is at least one of the following: a barcode, a QR code, a near-field communication tag, or any combination thereof. 29. The method of claim 27, wherein the identification information comprises at least one of the following: the manufacturing date of the diagnostic instrument; the expiration date of the diagnostic instrument; the analyte used for testing by the instrument; identification information about the test subject; patient condition information; or any combination thereof. 30. The method of claim 27, wherein the determining step further comprises analyzing the portion of the pre-used digital image containing the identification marker to determine the identification information and, at least in part based on the identification information, determining whether the diagnostic instrument is in use. 31. A diagnostic instrument for identifying multiple test results by testing a single patient fluid, the diagnostic instrument comprising: Instrument casing; Color references, including multiple reference samples of different colors other than white, are attached to or associated with the instrument housing for determining the test results from digital images of the diagnostic instrument; and Multiple test media, which are attached to the housing, contain a color-changing reagent that changes color in the presence of a specific analyte in a biological sample. 32. The diagnostic instrument of claim 31, wherein the plurality of test media are arranged in a plurality of test-specific sequences. 33. The diagnostic instrument of claim 32, wherein the instrument housing includes a paddle with a handle and a plurality of recesses disposed on the paddle for receiving the plurality of test media. 34. The diagnostic instrument of claim 32, further comprising an identification mark disposed on the instrument housing containing or associated with identification information about the diagnostic instrument, the identification information including at least one of the following: the manufacturing date of the instrument, the expiration date of the instrument, the analyte tested by the instrument, identification information about the test subject, the patient's condition, or any combination thereof. 35. The diagnostic instrument of claim 34, wherein the identification mark comprises at least one of the following: a barcode, a QR code, a near-field communication tag, or any combination thereof. 36. The diagnostic instrument of claim 31, wherein the plurality of test media includes a superhydrophobic coating for preventing fluid from dripping from the test media. 37. A system for reading diagnostic test results, the system comprising: A diagnostic instrument comprising a paddle, a color reference of multiple reference samples of different colors mounted on the paddle, and multiple test media mounted on the paddle, each test media containing a reagent that changes color in the presence of a specific analyte in a biological sample; and A portable electronic device comprising a camera sensor for capturing digital images of at least a portion of the diagnostic instrument and a processor configured to: Identify at least one of the reference samples other than the white reference sample and at least one of the test media in the digital image of the diagnostic instrument; Determine the visible camera captured color of the reference sample and the visible camera captured color of at least one test medium; Color correction is performed on the visible camera-captured color of the at least one test medium based on a correction factor derived at least partially from the visible camera-captured color of the at least one reference sample to determine the corrected test medium color; and The test results are determined by comparing the color of the calibrated test medium with a set of possible test medium colors corresponding to a predetermined analyte concentration to determine the analyte concentration of the biological sample being tested. 38. The system of claim 37, wherein the plurality of test media are arranged in a plurality of test-specific sequences. 39. The system of claim 37, further comprising an identification tag associated with the portable electronic device, wherein the digital image contains at least a portion of the identification tag. 40. The system of claim 39, wherein the processor is configured to identify the identification mark and verify the diagnostic instrument based on identification information contained on or associated with the identification mark. 41. The system of claim 37, further comprising a data transmitter associated with the portable electronic device, the data transmitter being configured to transmit at least a portion of the test results to an external source. 42. The system of claim 37, further comprising a visual display for displaying instructions for using the system or for displaying test results. 43. A portable electronic device for analyzing digital images from a diagnostic instrument, the portable electronic device comprising: At least one processor; At least one display device; At least one camera sensor; and At least one computer-readable medium including program instructions that, when executed by the at least one processor, cause the portable electronic device to: The camera sensor captures a digital image of at least a portion of the diagnostic instrument that has been exposed to a biological sample. The diagnostic instrument includes at least one color reference comprising a plurality of reference samples of different colors and at least one test medium containing a reagent that changes color in the presence of a specific analyte in the biological sample. Identify at least one of the reference samples other than the white reference sample in the digital image for use with the at least one medium in the diagnostic instrument; Determine the explicit camera-captured color of the reference sample in the digital image and the explicit camera-captured color of the at least one test medium; Color correction is performed on the visible camera-captured color of the at least one test medium based on a correction factor derived at least partially from the visible camera-captured color of the reference sample to determine the corrected test medium color; and The test results are determined by comparing the color of the calibrated test medium with a set of possible test medium colors corresponding to a predetermined analyte concentration to determine the analyte concentration of the biological sample being tested. 44. The portable electronic device of claim 43, wherein the program instructions further cause the portable electronic device to display usage instructions on the display of the portable electronic device, and wherein the usage instructions explain to the user how to expose the diagnostic instrument to the biological sample or how to capture the digital image of the diagnostic instrument. 45. The portable electronic device of claim 44, wherein the usage instructions are displayed in conjunction with the video signal of the diagnostic instrument provided by the camera sensor of the portable electronic device. 46. The portable electronic device of claim 43, further comprising a timer, wherein the program instructions further cause the portable electronic device to: Instruct the user to expose the diagnostic instrument to the biological sample; The predetermined preferred exposure time is measured using the timer; and The user is instructed to capture the digital image with the camera sensor after the predetermined preferred exposure time has elapsed. 47. The portable electronic device of claim 46, wherein the program instructions further cause the portable electronic device to: The actual exposure time is measured using the timer, the actual exposure time being the time between when the user exposes the diagnostic instrument to the biological sample and when the digital image captured by the diagnostic instrument is obtained; and The exposure time is corrected based on the difference between the predetermined preferred exposure time and the actual exposure time. 48. The portable electronic device of claim 47, wherein the program instructions further cause the portable electronic device to perform color correction on the visible camera-captured color of the at least one test medium based on the corrected exposure time. 49. The portable electronic device of claim 43, further comprising a data input device, wherein the program instructions further cause the portable electronic device to: Receive patient report information from the data input device; and The test results are compared with the patient record information to determine possible patient conditions.