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WO1998035262A1 - Spectroscopie infrarouge pour l'imagerie medicale - Google Patents

Spectroscopie infrarouge pour l'imagerie medicale Download PDF

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Publication number
WO1998035262A1
WO1998035262A1 PCT/CA1998/000092 CA9800092W WO9835262A1 WO 1998035262 A1 WO1998035262 A1 WO 1998035262A1 CA 9800092 W CA9800092 W CA 9800092W WO 9835262 A1 WO9835262 A1 WO 9835262A1
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WO
WIPO (PCT)
Prior art keywords
infrared
channel
spectral
imaging module
channels
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CA1998/000092
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English (en)
Inventor
Ryan S. Raz
Gordon Rosenblatt
Daniel S. Maclean
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Morphometrix Technologies Inc
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Morphometrix Technologies Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Morphometrix Technologies Inc filed Critical Morphometrix Technologies Inc
Priority to CA002279945A priority Critical patent/CA2279945A1/fr
Priority to AU59773/98A priority patent/AU5977398A/en
Publication of WO1998035262A1 publication Critical patent/WO1998035262A1/fr
Priority to US09/368,521 priority patent/US6181414B1/en
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G01N15/1429—Signal processing
    • G01N15/1433—Signal processing using image recognition
    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B27/00—Optical systems or apparatus not provided for by any of the groups G02B1/00 - G02B26/00, G02B30/00
    • G02B27/10—Beam splitting or combining systems
    • G02B27/1006—Beam splitting or combining systems for splitting or combining different wavelengths
    • G02B27/1013—Beam splitting or combining systems for splitting or combining different wavelengths for colour or multispectral image sensors, e.g. splitting an image into monochromatic image components on respective sensors
    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B27/00—Optical systems or apparatus not provided for by any of the groups G02B1/00 - G02B26/00, G02B30/00
    • G02B27/10—Beam splitting or combining systems
    • G02B27/14—Beam splitting or combining systems operating by reflection only
    • G02B27/141—Beam splitting or combining systems operating by reflection only using dichroic mirrors
    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B27/00—Optical systems or apparatus not provided for by any of the groups G02B1/00 - G02B26/00, G02B30/00
    • G02B27/10—Beam splitting or combining systems
    • G02B27/14—Beam splitting or combining systems operating by reflection only
    • G02B27/144—Beam splitting or combining systems operating by reflection only using partially transparent surfaces without spectral selectivity
    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B27/00—Optical systems or apparatus not provided for by any of the groups G02B1/00 - G02B26/00, G02B30/00
    • G02B27/10—Beam splitting or combining systems
    • G02B27/14—Beam splitting or combining systems operating by reflection only
    • G02B27/145—Beam splitting or combining systems operating by reflection only having sequential partially reflecting surfaces
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/69—Microscopic objects, e.g. biological cells or cellular parts
    • G06V20/693—Acquisition
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/30—Writer recognition; Reading and verifying signatures
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30024—Cell structures in vitro; Tissue sections in vitro

Definitions

  • the present invention relates to Near Infrared (NIR) spectroscopy and more particularly to a multi -channel spectral imaging module utilizing NIR for discriminating between normal and pre-cancerous cells prepared in the form of cells or cell groupings on a microscope slide.
  • NIR Near Infrared
  • Pap i.e. Papanicolaou
  • the Pap test is a screening test for evidence of pre- cancerous lesions in exfoliated cervical cells.
  • the Pap test involves a tedious, manual examination of tens of thousands of cervical epithelial cells, and as a result is costly to apply and is subject to human error. Nevertheless, the Pap test has an enviable record of reducing cervical cancer mortality in the countries where it is applied. Thus, an automated alternative has been eagerly sought .
  • image analysis typically comprises a series of four steps.
  • the third step is known as feature extraction. Each of the segmented regions or objects in the image is subjected to a range of mathematical measures that seek to encapsulate the visual appearance in numerical form.
  • the fourth step known as classification involves using the numerical features to arrive at some type of conclusion about the object's identity.
  • NIR spectroscopy is an established technique for the extraction of quantitative measures in a wide variety of materials. Recently, NIR spectroscopy has been applied to human tissue samples in order to discriminate between cancerous or pre-cancerous tissue and normal tissue.
  • NIR-based cancer screening protocols including a screening protocol for the early detection of pre-cancerous lesions of the uterine cervix and carcinomatous breast tissue.
  • the present invention provides a multi-channel spectral imaging module utilizing NIR spectroscopic techniques to produce a rapid and effective discrimination between normal and pre- cancerous cells prepared in the form cells or cell groupings on a microscope slide or similar sub-structure .
  • the subject invention is intended to function as part of an automated system comprising components described in co- pending patent applications entitled Automated Scanning of Microscope Slides International Patent Application No . CA96/00475 filed July 18, 1996, Pipeline Processor for Medical and Biological Applications U.S. Patent Application No. 08/683,440 filed July 18, 1996, Multi-Spectral Segmentation International Patent Application No. CA96/00477 filed July 18, 1996, Neural- Network Assisted Multi-Spectral Segmentation International Patent Application No. CA96/00619 filed September 18, 1996, Automated Focus System International Patent Application No. CA96/00476 filed July 18, 1996, Window Texture Extraction International Patent Application No.
  • the present invention comprises a multichannel spectral imaging module for an automated testing system for cytological applications.
  • one or two of the channels in the imaging system comprise NIR (Near Infrared) channels.
  • the NIR channels augment the visible spectrum images produced by a multi -spectral camera system and provide new and useful channels of information.
  • the NIR channels are used to improve segmentation performance, to create a new set of features for classification, or as discrimination measures independent of the visible light channels.
  • a pair of differential NIR channels are utilized to provide a high-speed and real-time scan of cellular material to quickly discriminate between normal and abnormal cells or tissue and may be extended to other important diagnostic properties of the cells.
  • the NIR channels are effective for producing rapid and effective discrimination between normal and pre-cancerous cells prepared in the form cells or cell groupings on a microscope slide or similar sub-structure .
  • the present invention provides a multi-channel spectral imaging module for an automated testing system for cytological application, said multi-channel spectral imaging module comprising: (a) a light source module for illuminating a cytological specimen, said light source including a visible light source and an infrared light source and a control input for actuating said visible and infrared light sources; (b) an optical imaging module for receiving illuminated images of said cytological specimen and including a lens system for focussing said illuminated images; (c) a prism module for receiving said illuminated images from said optical imaging module, said prism module including three prism elements for producing three respective image channels in the visible spectrum and a fourth prism element for producing an image channel in the infrared spectrum, and said prism module further including a digitizer for each of said channels for converting the image into an output signal.
  • the present invention provides a method for generating multi-spectral image date for a cytological specimen, said method comprising the steps of: (a) exposing said cytological specimen to a burst of broad-band light; (b) separating said burst of broad-band light images into a plurality of spectral bands; (c) simultaneously capturing an image for each of said spectral bands and generating electrical signals corresponding to each of said captured spectral images; (d) converting the electrical signals corresponding to said captured spectral images into a data form suitable for further processing by an automated testing system; (e) exposing said cytological specimen to a burst of light in an infrared spectral band; (f) simultaneously capturing an image in said infrared spectral band and an generating electrical signal corresponding to said captured infrared spectral image; (g) converting the electrical signal corresponding to said captured infrared spectral image into a data form suitable for further processing by an automated testing system.
  • Fig. 1 shows in diagrammatic form a multi-channel spectral imaging module according to the present invention
  • Fig. 2 shows the prism assembly of Fig. 1 in more detail ;
  • Fig . 3 shows the arrangement of CCD arrays for the imaging module of Fig. 1;
  • Fig. 4 shows the illumination mixer of Fig. 1 in more detail ;
  • Fig. 5 depicts linear discriminant analysis utilizing outputs from the multi -channel spectral imaging module according to the present invention
  • Fig. 6 shows threshold identification based on outputs from the multi-channel spectral imaging module according to the present invention
  • Fig. 7 shows composite feature measurement based on the outputs from the multi -channel spectral imaging module according to the present invention
  • Fig. 8 an embodiment of the multi -channel spectral imaging module according to the present invention in which the NIR channels are operated in a differential mode
  • Fig. 9 shows the known Infrared spectra of cervical tissues in the asymmetric phosphate stretching region.
  • the automated system for cytological testing as described in the co-pending applications by the common owner of the present invention as outlined above utilizes three narrowly defined optical bands in the visible . range to characterize the cells under examination.
  • the three bands are chosen so as to maximize the optical contrast between the nucleus and cytoplasm of the cell and the background material.
  • the information obtained from three bands is used to generate a segmentation map of the image on a pixel -by-pixel basis.
  • the segmentation map is subjected to further processing to improve the integrity and quality of the captured information.
  • a feature extraction operation is performed.
  • Feature extraction involves subjecting each of the segmented regions or objects in the image to a range of mathematical measures that seek to encapsulate the visual appearance in numerical form.
  • classification involves using the numerical features to arrive at some type of conclusion about the object's identity. It will be appreciated that the utilization of three channels of information provides an information foundation which ensures the quality and reliability of the captured information during the various processing steps performed by the automated system.
  • the present invention comprises a multi-channel spectral imaging module for the multi- spectral camera system described in the co-pending patent application entitled Multi-Spectral Imaging System and Method for Cytology International Patent Application No. CA97/00318 filed May 9, 1997 by the common owner of the subject invention.
  • the multi -spectral camera as described in the co-pending application comprises an electro-optical system that creates digitized, spectrally-separated images for computer acquisition, display and analysis.
  • the system operates with high resolution and at high speed, simultaneously producing three, spectrally-resolved, spatially coincident micro-graphic images for capture and storage by computer.
  • the simultaneous acquisition of spectrally-resolved images in the visible light region permits the high-speed application of polychromatic stain protocols in automated analysis procedures.
  • the simultaneous capture of the images also ensures that image registration is maintained for image processing operations which as will be appreciated is a problem in systems which serially capture images.
  • the multi -channel spectral imaging module comprises one or two NIR (Near Infrared) channels.
  • the NIR channels are utilized to augment the visible spectrum images produced as per the common applicant's multi- spectral camera system to provide a new and useful channel of information.
  • the near- infrared absorption properties of the cervical epithelial cells may be integrated into this technique to yield a new channel of information.
  • normal epithelial nuclei reach an absorption plateau in the range of 1215 cm -1 while malignant epithelial nuclei near an absorption peak according to known studies (ex., PTT Wong,et al . Applied Spectroscopy 48(7) 1058 (1993)).
  • the ratio of absorbencies, measured on bulk material, is approximately 1.8 in a 5 cm “1 range centred at this frequency. Nearby, as shown in Fig. 9, the absorbencies of the normal and malignant materials converge at 1240 cm "1 , providing a suitable channel for response normalization. These narrow NIR bands are ideally exploited for discriminative purposes in the context of present invention.
  • the NIR channels are used to improve segmentation performance, to create a new set of features for classification, or as discrimination measures on their own.
  • restricting the use of the NIR channels to regions of the samples that contain nuclear material also improves the effective signal-to- noise ratio of the measurement over bulk tissue measurements thereby improving the discrimination capability of the system.
  • a pair of differential NIR channels i.e. the 1215 cm "1 band providing an interrogation channel and the 1240 cm " 1 band providing a reference channel
  • this embodiment may be extended to other important diagnostic properties of the cells.
  • the multi-spectral imaging module 10 comprises an optical imaging module 12, a prism module 14, a series of CCD (Charge Coupled Device) array sensors 16, and an illumination mixer 18.
  • CCD Charge Coupled Device
  • the principal function of the optical imaging module 12 is gathering a microscope image of a specimen S (e.g. a cytological specimen S placed on a suitable carrier such as a slide C) and enlarging the microscopic image with minimal monochromatic or chromatic aberrations.
  • the optical imaging module 12 comprises two lens systems: an objective lens 22 and a telan lens 24.
  • the objective lens 22 is designed for infinite-conjugate operation meaning that the object is placed in the focal plane of the objective lens 22 and a real image is produced at an infinite distance away on the optical axis 23.
  • the objective lens 22 alone carries all of the monochromatic and chromatic error corrections and produces a flat-image field over the area of interest.
  • the telan lens 24 is used to gather this infinite-conjugate image from the objective lens 22 and reconstruct a real magnified image MI a short distance from the optical imaging module 12.
  • the magnified image MI is optically coupled to the prism module 14.
  • the magnifying power of optical imaging module 12 is expressed as the negative of the ratio of the two effective focal lengths of the objective 22 and telan 24 lenses, as follows:
  • magnification is independent of tube length unlike the older 160 mm DIN standard for microscopes as will be familiar to those skilled in the art .
  • the prism module 14 is optically coupled to the output of the optical imaging module 12 to receive the magnified image MI.
  • the prism module 14 comprises an optical prism assembly 20 which is used to create five-spectrally resolved channels 17a to 17e.
  • the channels 17 for the imaging system comprise three visible-light channels 17a, 17b and 17c, and single NIR channel 17d or a differential NIR channel pair 17d and 17e.
  • the visible- light channels 17a, 17b, 17c comprise narrow band channels having centre wavelengths 530 nm, 577 nm and 639 nm as described in co- pending International Patent Application No . CA97/00318 filed May 9, 1997.
  • the prism assembly 20 comprises a set of five interlocking glass prisms 21, with each prism 21a, 21b, 21c, 21d, 21e, 21f corresponding to a respective channel 17a, 17b, 17c, 17d, 17e and 17f.
  • Each glass prism 21 includes a dichroic, multi-layer interference band-pass optical filter 23 on one of its surfaces.
  • the prism assembly 20 receives the magnified image MI projected from the telan lens 24 in the optical imaging module 12 and creates a set of five equivalent images that have been filtered to reject all but the five bands of the respective channels 17.
  • the .prism assembly 20 re-directs each one of the five images to the associated CCD array sensor 16a along five separate paths (i.e. channels 17) to accomplish a low-loss spatial separation.
  • the prism assembly 20 provides simultaneous spectral and spatial separation of the magnified image MI from the optical module 12 with high through-put, low optical energy loss, minimal distortion and minimal mis-registration difficulties .
  • the CCD sensor arrays 16 are coupled to the prism module 14 and arranged to collect and digitize the spectrally- resolved images projected from the associated prism element 21 for each channel 17.
  • the CCD sensor arrays 16 comprise charge coupled devices and are shown individually as 16a, 16b, 16c, 16d, and 16e in Fig. 1.
  • a sensor array 16 is provided for each channel 17.
  • the CCD sensor arrays 16 operate in parallel to simultaneously digitize the respective images from the five channels 17a to 17e.
  • the digitized images are then transferred over a set of fibre optical links (not shown) to the subsequent stages of the automated testing system (not shown) for further processing as described in the co-pending patent applications outlined.
  • each CCD sensor array 16 is mounted on a respective micro-positioning device 19, shown individually as 19a, 19b, 19c, 19d and 19e.
  • the micro-positioning devices 19 are used to align the CCD sensor arrays 16 and bring the images form each respective channel 17 into registration with the associated CCD 16. Once the initial calibration is completed and the CCD arrays 16 are registered with the image paths, it is usually not necessary to adjust the alignment again.
  • an infrared light source 26 is provided in addition to a visible light source 28.
  • the visible light source 28 comprises a stroboscopic flash lamp which provides the light source for the three visible optical channels 17a to 17c.
  • the infrared light source 26 may comprise a suitable commercially available infrared lamp or a tunable laser system.
  • the illumination mixer 18 combines the output from the visible light source 28 with the output from the infrared radiation source 26. As shown in Fig. 4, the illumination mixer 18 comprises a beam-splitter 30 and a shutter 32.
  • the beam-splitter 30 is arranged to mix the outputs from the two radiation sources 26 and 28 in order to provide optimal illumination of the specimen S.
  • the shutter 32 is used to selectively couple the output from the infrared light source 26 to the optical imaging module 12. The actuation of the shutter 32 is synchronized with the strobing of the lamp 28.
  • the information generated from the NIR channel (s) 17d and 17e is exploited in three ways: (1) to improve segmentation performance; (2) to provide a new set of features for classification; or (3) to provide an independent discrimination measure .
  • the multi-spectral segmentation procedure comprises a hardware-encoded analysis routine embedded in the FPGA logic of a special-purpose computer.
  • several processing steps are applied to the images.
  • images from each of the three visible light channels i.e. 17a, 17b, 17c
  • the absorption maps show the properties of each of imaged pixels independently of material thickness.
  • a new fourth absorption map and a new fifth absorption map are produced to show the material properties associated with the NIR formed images of the specimen S.
  • the NIR channels 17d and 17e add two new axes of information to a multidimensional space representing the material properties of the specimen S. If enough examples of nuclei and cytoplasm are studied, this multi-dimensional space will yield discrimination information expressed in terms of the occupation of different regions of this multi-dimensional space. Thus, for every new pixel that enters the system for analysis, a point in this space can be defined and, based on the region that it occupies, its identity may be determined. This is illustrated by Fig. 5 which depicts the application of linear discriminant analysis techniques to a feature space 100 having three dimensions.
  • the feature space 100 comprises upper 101 and lower 102 portions which are separated by a discrimination boundary 103.
  • the upper region 101 is associated with class I while the lower portion 102 is associated with class II.
  • a segmentation technique that employs a hardware-embedded linear discriminant analysis reduces the degree of error typically associated with segmentation decisions by correlating a series of observations concerning the distribution pattern of material absorption.
  • this technique opens the door to a multiplicity of similar types of discriminant analysis.
  • this type of algorithm can undergo a continual improvement by the adjustment of a table of coefficients that describe the decision hyper- surface without the necessity of altering the system architecture .
  • the two NIR channels 17d and 17e are used to provide new sets of features for the specimen S.
  • the mathematical transformations applied to the outputs from the three visible channels 17a to 17c may be applied with equal utility to the outputs from the NIR channels 17d and 17e.
  • morphological, textural , densitometric, and contextual features may be extracted from the NIR channel (s) 17d and 17e.
  • a number of correlating features may be generated through comparisons with the three visible light channels 17a, 17b or 17c and the NIR channels 17d, 17e.
  • the outputs from the NIR channels 17d and 17e are also utilized to provide an independent discrimination measure as depicted in Fig. 6. For instance after absorption baselines are calculated, the automated testing system uses a threshold 111 to determine whether any of the resultant segmented objects generated from in specimen S is abnormal 112, whereas normal objects take the distribution denoted by 113.
  • the discrimination measures from the NIR channels 17d, 17e can form the basis of an automated decision process or may be included in a computer-aided review of the sample for full diagnosis by a cytotechnologist . Another application of information generated from the NIR channels 17d, 17e is as part of a wide set of statistical measures for the specimen S as a whole.
  • a normal NIR feature representation is indicated by the distribution at 121
  • an abnormal NIR feature representation is indicated by the distribution at 122.
  • the two NIR channels 17d and 17e are operated in a differential mode to provide a real-time discrimination between normal and abnormal cellular material in the specimen S (or between any two biological states that exhibit differences in this or any other pair of NIR bands) .
  • the first NIR channel 17d provides an interrogation signal channel 50 and the second NIR channel 17e provides a reference signal channel 51.
  • the interrogation 50 and reference 51 channels form the inputs for a differential amplifier 52.
  • the differential ampli ier 52 produces an output 53 based on the difference between the interrogation 50 and the reference 51 signals.
  • the output 53 from the differential amplifier 52 provides one input for a division amplifier 54.
  • the other input of the division amplifier 54 is coupled to the reference channel 51.
  • the division amplifier 54 produces a pixel signal denoted by 60 at the output 55.
  • the reference channel 51 In operation, local variations in the thickness of the specimen S and/or variations in the illumination intensity are compensated- for by the reference channel 51.
  • the interrogation signal 50 is subtracted from the reference signal 51 and the resulting signal 53 is normalized with the reference signal 51 by the division amplifier 54.
  • results of the high-speed scan can then be subjected to a more detailed analysis by a computing system, and images of the suspicious material could be displayed to a human review on a monitor or the regions found could be flagged for further study by conventional means.

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Abstract

Module imageur spectral à canaux multiples pour système d'essai automatisé utilisé dans des applications cytologiques. Ledit module génère quatre canaux d'images numérisées d'un échantillon cytologique destiné à être traité dans ledit système d'essai automatisé. Il comprend une source de lumière visible et une source de lumière infrarouge, un module d'imagerie optique, un module à prismes et un étage de sortie. L'échantillon cytologique est balayé par impulsions stroboscopiques par les sources de lumière visible et infrarouge et les images éclairées de l'échantillon sont concentrées et couplées au modules à prismes par le module d'imagerie optique. Le module à prismes divise l'image éclairée en quatre canaux comprenant trois canaux de lumière visible et un canaux infrarouge. L'étage de sortie comprend un capteur à CCD pour chaque canal. Ledit capteur à CCD numérise l'image pour le canal et produit une sortie destiné à être encore traitée. La sortie numérisée provenant du canal infrarouge produit des informations supplémentaires qui sont utilisées par le système d'essai automatisé. Les informations supplémentaires dérivées du canal infrarouge comprennent des informations de segmentation, des caractéristiques d'identification nouvelles pour l'échantillon, et des mesures de discrimination indépendantes des canaux de lumière visible. Dans un autre mode de réalisation, un cinquième canal est prévu pour une sortie infrarouge de référence et les deux canaux infrarouge sont exploités en mode différentiel.
PCT/CA1998/000092 1997-02-06 1998-02-06 Spectroscopie infrarouge pour l'imagerie medicale Ceased WO1998035262A1 (fr)

Priority Applications (3)

Application Number Priority Date Filing Date Title
CA002279945A CA2279945A1 (fr) 1997-02-06 1998-02-06 Spectroscopie infrarouge pour l'imagerie medicale
AU59773/98A AU5977398A (en) 1997-02-06 1998-02-06 Infrared spectroscopy for medical imaging
US09/368,521 US6181414B1 (en) 1998-02-06 1999-08-05 Infrared spectroscopy for medical imaging

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US3745497P 1997-02-06 1997-02-06
US60/037,454 1997-02-06

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US09/368,521 Continuation US6181414B1 (en) 1998-02-06 1999-08-05 Infrared spectroscopy for medical imaging

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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2005088385A1 (fr) * 2004-03-10 2005-09-22 Raytheon Company Systeme de capteur a deux bandes utilisant un separateur de faisceau selectif en longueur d'onde
US7019296B2 (en) 2000-10-13 2006-03-28 Chemimage Corporation Near infrared chemical imaging microscope
US7046359B2 (en) 2004-06-30 2006-05-16 Chemimage Corporation System and method for dynamic chemical imaging
WO2007064431A1 (fr) * 2005-11-30 2007-06-07 Corning Incorporated Separateur de lumiere
US7580126B2 (en) 2004-06-30 2009-08-25 Chemimage Corp. Method and apparatus for producing a streaming Raman image of nucleation, aggregation, and chemical interaction
CN109813716A (zh) * 2017-11-22 2019-05-28 北京汉能光伏投资有限公司 太阳能组件故障检测系统和方法

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US3806257A (en) * 1973-05-04 1974-04-23 Corning Glass Works Operator viewing optics for a slide classification system
EP0174778A1 (fr) * 1984-08-30 1986-03-19 Rank Cintel Limited Dispositif de traitement individuel d'images optiques de longueur d'onde différente
DE19623821A1 (de) * 1995-06-14 1996-12-19 Asahi Seimitsu Kk Prismen-Farbteiler

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US3806257A (en) * 1973-05-04 1974-04-23 Corning Glass Works Operator viewing optics for a slide classification system
EP0174778A1 (fr) * 1984-08-30 1986-03-19 Rank Cintel Limited Dispositif de traitement individuel d'images optiques de longueur d'onde différente
DE19623821A1 (de) * 1995-06-14 1996-12-19 Asahi Seimitsu Kk Prismen-Farbteiler

Cited By (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7436500B2 (en) 2000-10-13 2008-10-14 Chemimage Corporation Near infrared chemical imaging microscope
USRE39977E1 (en) 2000-10-13 2008-01-01 Chemimage Corporation Near infrared chemical imaging microscope
US7317516B2 (en) 2000-10-13 2008-01-08 Chemimage Corporation Near infrared chemical imaging microscope
US7061606B2 (en) 2000-10-13 2006-06-13 Chem Image Corporation Near infrared chemical imaging microscope
US7123360B2 (en) 2000-10-13 2006-10-17 Chemimage Corporation Near infrared chemical imaging microscope
US7268861B2 (en) 2000-10-13 2007-09-11 Chemimage Corporation Near infrared chemical imaging microscope
US7019296B2 (en) 2000-10-13 2006-03-28 Chemimage Corporation Near infrared chemical imaging microscope
US7268862B2 (en) 2000-10-13 2007-09-11 Chem Image Corporation Near infrared chemical imaging microscope
US7298484B2 (en) 2004-03-10 2007-11-20 Raytheon Company Dual-band sensor system utilizing a wavelength-selective beamsplitter
WO2005088385A1 (fr) * 2004-03-10 2005-09-22 Raytheon Company Systeme de capteur a deux bandes utilisant un separateur de faisceau selectif en longueur d'onde
US7046359B2 (en) 2004-06-30 2006-05-16 Chemimage Corporation System and method for dynamic chemical imaging
US7317526B2 (en) 2004-06-30 2008-01-08 Chem Image Corporation System and method for dynamic chemical imaging
US7580126B2 (en) 2004-06-30 2009-08-25 Chemimage Corp. Method and apparatus for producing a streaming Raman image of nucleation, aggregation, and chemical interaction
WO2007064431A1 (fr) * 2005-11-30 2007-06-07 Corning Incorporated Separateur de lumiere
CN109813716A (zh) * 2017-11-22 2019-05-28 北京汉能光伏投资有限公司 太阳能组件故障检测系统和方法
CN109813716B (zh) * 2017-11-22 2024-03-08 东君新能源有限公司 太阳能组件故障检测系统和方法

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