CN107106104A - The system and method analyzed for orthopaedics and treat design - Google Patents

Abstract

The system and method that the present invention covers the efficiency of the treatment plan for being modified to orthopaedic disease.The invention provides a variety of analysis tools.One such analysis tool allows to carry out design personalized treatment plan using the quantitative measurment and the information related to patient of related orthopaedics structure, is wherein obtained in the 3D models for the orthopaedics structure that the quantitative measurment is built from the radiographic images using the structure.Another analysis tool allows the personalized implant model of the measuring and design based on patient.Personalized treatment plan and implant model can be assessed based on biomechanical analysis by using another analysis tool.The system can use assessment result to change and improve treatment plan and implant model.One the build tool can be used to build implant model for example, by 3D printing.The system also has the ability that report is generated for treatment plan.

Description

Systems and methods for orthopedic analysis and treatment design

Cross References to Related Applications

This application claims priority to United States Provisional Patent Application No. 62107296, filed January 23, 2015, in the United States Patent and Trademark Office (USPTO).

Background technique

Whether for surgical or non-surgical treatments, orthopedic treatments require extensive pre-treatment planning. The invention disclosed herein automates the precise treatment planning process through a personalization step that takes into account each individual patient's orthopedic profile and other relevant information. It provides physicians with an all-inclusive solution. The invention has been implemented using patient information from different sources combined with 3D printing to facilitate patient/physician education and understanding, as well as provide precise treatment solutions for better patient care. For optimal clinical workflow, the system streamlines all aspects of orthopedic care: diagnosis, treatment planning and assessment, pre-surgical planning, and post-treatment follow-up and assessment.

Contents of the invention

One form of the invention is a system for planning orthopedic treatment. A basic embodiment of such a system includes two main components: a modeling module that constructs a 3D model of the body segment relevant to the planned treatment from radiographic images; and an analysis module that includes the following analysis tools: (1) an interactive visualization tool that allows the user of the system to visualize and edit the 3D model, (2) a quantification tool to obtain measurements of the 3D model relevant to the treatment, (3) a planning tool to use generating a personalized surgical plan based on the measurements, and (4) an evaluation tool for evaluating the surgical plan using one or more biomechanical analyses. In this basic embodiment of the invention, the planning tool allows the output of the evaluation tool to be used to modify the surgical plan.

In another embodiment, the system includes: an implant design tool for designing an implant model based on measurements obtained from a 3D model of the patient; an evaluation tool that allows the use of one or more biomechanical analyzes to evaluate the implant model; and a planning tool that allows the output of the evaluation tool to be used to modify the implant model.

One embodiment of the invention includes an assessment tool for non-surgical treatment assessment and post-treatment assessment. The system may also include other analysis tools, including: (1) a diagnostic tool that gives an orthopedic diagnosis based on radiographic images and other relevant information according to predefined criteria, and (2) a construction tool that allows patient-based A 3D model or implant model to construct a physical object.

The system may also include a disease module that allows the user to select a predefined workflow for a particular orthopedic disease that is automatically invoked in a predefined order appropriate to the treatment plan for the disease One or more analysis tools.

The present invention also encompasses various methods for computer-aided treatment planning for orthopedic disorders, as well as many other variations not covered by this Summary. The exact scope of the invention is set forth in the claims.

Description of drawings

Figure 1 depicts the high-level system architecture of one embodiment of the present invention.

Figure 2 shows one form of implementation of the acquisition means used in the present invention.

Figure 3 illustrates exemplary components of the 3D modeling functionality of the present invention.

Fig. 4 illustrates a disease type thread and an analysis function thread of a specific embodiment of the present invention.

FIG. 5 illustrates several exemplary portions of the visualization component of the present invention, Interactive Visualization 320 .

FIG. 6 illustrates exemplary portions of one embodiment of the surgical planning component of the present invention, pre-operative planning 330 .

FIG. 7 shows exemplary portions of one embodiment of an evaluation component of the present invention, biomechanical analysis 340 .

FIG. 8 shows exemplary portions of one embodiment of the implant design component of the present invention, personalization 350 .

FIG. 9 shows exemplary parts of one embodiment of a building part of the present invention, 3D printed 360 .

Figure 10 shows several exemplary parts of the output component of the present invention.

Figure 11 illustrates an embodiment of the present invention.

detailed description

The present invention is an interactive quantitative analysis system that provides orthopedic surgeons with automatic or semi-automatic tools for rendering patient-specific treatment decisions and solutions. System 100 in FIG. 1 illustrates one embodiment of components useful in the present invention. The system consists of an acquisition module 110 for acquiring orthopedic images, an archiving module 120 and a patient recording module 130 for processing patient input information for further processing. The preprocessing of the input information is accomplished by the relevant input information module 140 , the radiographic image module 150 and the modeling module 160 . Personalized decisions and treatment solutions are based on user selection module 170 from one of two threads (disease type thread 173 and analysis function thread 175). Output is generated from the output 180 mechanism and reporting module 190 .

A user may, for example, select an orthopedic disease from the disease type thread 173 to start an interactive workflow based on disease type that has been developed to ensure an optimal clinical workflow. Each disease type selection typically corresponds to a workflow stored in the workflow library. A predefined workflow automatically invokes one or more analysis functions or tools in the analysis module in an order appropriate for the disease. Alternatively, the user may select a function or tool from the analysis function thread 175 to perform a specific analysis for a different type of disease. Physicians can choose from any thread to arrive at a personalized decision and treatment solution for the patient. Physicians can utilize output 180 to aid physician/patient education and understanding, as well as to facilitate precise treatment solutions. The reporting module 190 will use the archive 120 and patient record 130 mechanisms to generate reports and archive data. The reporting function can also be designed as a tool of the analysis module.

Figure 2 illustrates a schematic diagram depicting one exemplary embodiment of a general method for accessing and retrieving patient information from different sources for further processing. This embodiment consists of three main components: Acquisition 110 , Archive 120 and Patient Record 130 . Acquire 110 is the acquisition of patient input data for further processing. Patient input data, such as medical images, are acquired from different acquisition modalities including, but not limited to, X-ray, CT, MR imaging, functional MRI, perfusion MRI, bone densitometry, and electromyography (EMG). Patient data can also be retrieved from archives or other databases. Archive 120 may include internet cloud 123 storage, local offline archive 125, and/or Picture Archiving and Communication System (PACS) 127, where patient radiographic information may be retrieved and archived for analysis. Physicians can also use data from the Internet cloud 123 for collaborative research. Patient records module 130 may include several patient record systems, including, for example, hospital information system (HIS) 133, electronic medical record (EMR) 135, radiology information system (RIS) 137, and/or laboratory information system (LIS) 139 . Patient clinical data may be retrieved from one or more of these databases to assist in the analysis process. An input device such as a barcode reader 131 may be used to facilitate the data retrieval process. The acquisition module may also facilitate storage of new patient data (eg, personalized 3D models or implant models) generated by the system back into the patient database.

FIG. 3 illustrates an exemplary implementation for modeling module 160 . The modeling module creates a 3D digital model 270 of the selected bone structure. Unless otherwise stated, the term "3D model" is used in this patent to refer to a 3D digital, computer or virtual model of an orthopedic structure. The 3D model can be automatically created by using the module automatic model processing 210 . For this purpose, the system automatically segments and labels the 3D model based on the radiographic image of the patient. Here "segmenting" means the process of dividing a 2D image into different regions by delineating or contouring a region of interest (ROI) of a 3D model. "Labeling" means labeling areas of different parts of the delineated structure forming the 3D model. There are a variety of different segmentation algorithms useful for the purposes of the present invention including, for example, thresholding, region growing, clustering algorithms, edge detection, and model-based segmentation. Labeling is achieved by connected-component analysis using different optimization techniques.

The 3D model can also be created semi-automatically by using the module semi-automatic model processing 230 which allows the user to select a ROI for automatic segmentation or (by means of the system) to manually segment the 2D image. For example, the system can project a 2D image onto a touch screen, and the user can use a stylus to visually trace the outline of a bone segment. After the system completes the segmentation, the user can manually or automatically mark the segments of the 3D model.

If necessary or desired, the 3D model so generated can be manually edited using tools from the interactive model processing 250 and the module 3D model. An interactive model processing module is provided to the user to ensure that the constructed model is realistic and accurate. This module includes a set of editing tools for manual editing to improve 3D models in a real-time interactive environment. This is achieved through the interaction between the interactive model processing module and the 3D model 270, wherein the 3D model displays the edited 3D model in real time. This process can continue iteratively until a satisfactory result is reached.

The interactive model processing module allows editing of 3D models in 2D, 3D or higher dimensional spaces. There are various editing tools including, for example but not limited to, tools for adding or removing contours, tools for connecting or disconnecting contours, tools for editing points on contours, tools for automatically spreading curves , tools for smoothing curves, and tools for manual labeling.

The user selection module 170 in FIG. 1 is an important workflow direction module. 4 illustrates various exemplary components of modules that a user (ie, physician or clinician) may select to perform various clinical workflows. The disease type thread 173 consists of several predetermined clinical workflows, each designed for a specific disease, from orthopedic disease 1 to orthopedic disease N, thereby providing patients with individualized treatment solutions. Examples of orthopedic diseases include, but are not limited to, osteonecrosis, osteoarthritis, various types of fractures, and scoliosis. The predetermined clinical workflow may include one or more analysis functions from the analysis function thread 175 as well as other custom functions specific to the disease. The analysis function thread enables the physician to select from a series of specific analysis tools including, but not limited to, diagnosis 310, interactive visualization 320, pre-surgical planning 330, biomechanical analysis 340, personalization 350 and 3D Printed 360, they can be applied to patient information in order to perform a specific analysis function(s) on a patient's data or a disease condition.

Diagnostic tool 310 in FIG. 4 is a 2D diagnostic tool for detecting and distinguishing orthopedic abnormalities associated with various diseases. Such a diagnosis is based on the patient's imaging data retrieved from the radiographic image 150 , with or without other clinical data from the associated input information 140 . Several types of technical tools are used to detect and highlight diseased areas of bone tissue, referred to as "salient areas." Examples of such technological tools include artificial intelligence algorithms, such as artificial neural networks for computer vision, machine learning, and statistical pattern recognition and digital image processing. These techniques are employed to extract properties and features of salient regions associated with bone disease for diagnosis. Diagnostic tools can use the entire image or selected ROIs from the image. Significant regions can be permanently stored in archive 120 and/or patient record 130; and can be used for future machine diagnosis after approval by a physician as a disease-related abnormality.

For diagnostic purposes, many properties of salient regions can be analyzed, such as (1) quantitative measures, (2) texture descriptors, (3) anatomical spatial descriptors, and (4) other domain-specific information descriptors. Quantitative measurements are a set of quantifiable characteristics (such as size, shape, density, and various statistics of such measurements) that can be used to assess the presence or extent of bone abnormalities. Texture descriptors characterize the homogeneity of a region that can be used as a diagnostic indicator (eg degeneration or hardening). Anatomical space descriptors can be used to indicate the precise relative location of anatomical structures. For example, osteonecrosis treatment varies with location, and the size and location of necrotic lesions are important factors used to predict femoral head collapse in the early stages of the disease.

Interactive visualization tool 320 in FIG. 4 allows a user to perform real-time interactive visualization and editing of 3D models and/or 2D images. An exemplary embodiment for an interactive visualization tool is illustrated in FIG. 5 . It includes a manipulation module 470 that allows visualization and manipulation of 2D images and various 3D models retrieved from radiographic images 150, such as models 410 giving 3D surfaces, 3D anatomical models 430 and models giving 3D volumes 450. It also allows users to associate 3D models with 2D images. The interactive model editing module 490 also allows editing of the 3D model, if desired, for various purposes.

Surgical planning is an important aspect of the present invention, one embodiment of which is the pre-operative planning tool 330 in FIG. 4 . Pre-operative planning 330 is a platform for real-time interactive pre-operative planning. FIG. 6 illustrates an exemplary embodiment of a pre-operative planning module 330 that includes modeling 160 , quantification 500 , automatic planning 510 , interactive personalized planning 520 , and biomechanical analysis 340 .

An important aspect of surgical planning is obtaining specific quantitative measurements of the patient for whom surgery is being planned. For this purpose, in one embodiment as shown in FIG. 6 , the surgical planning module contains a quantitative tool 500 that extracts from the 3D model generated by modeling 160 for the patient the parameters needed for the surgical procedure. Quantitative measurement. In other embodiments, such quantitative tools may be stand-alone tools that may be utilized by surgical planning and other tools. Quantitative measurements and 3D models are then used for automatic planning 510 . The automated plan 510 generates a pre-surgical plan according to standard care protocols. The interactive personalized plan 520 provides the user with interactive editing tools to modify the pre-surgical plan into a more accurate personalized pre-surgical plan based on patient-specific data. Biomechanical analysis 340 will provide an assessment of pre-surgical planning. This enables the physician to assess the precision of the surgery, eg the stability criteria of THE surgery (see below).

The automatic planning tool 510 in FIG. 6 is a planning tool based on the 3D model built by the modeling module 160 and the quantitative measurements extracted by the quantitative 500 . The automated planning tool 510 then automatically generates a pre-surgical plan according to standard care protocols. For example, in one specific embodiment for total hip replacement (THR) surgery, the implant and An exact match is required between the patient's anatomy. For THR surgery, automated planning 510 takes 3D models of the patient's hip and leg from modeling 160 and extracts relevant quantitative measurements of the patient based on the 3D models. An automated planning tool then uses the standard THE protocol to generate a pre-surgical plan for THR that includes a standard implant model and surgical procedure. A physician user of the system then uses the interactive personalized plan 520 to review and, if necessary, edit the pre-surgical plan to generate an accurate and personalized pre-surgical plan for the patient. Then use Biomechanical Analysis 340 to simulate and test accurate individualized pre-surgical plans, especially implant models. The biomechanical analysis tool can generate modification recommendations for pre-surgical planning based on the biomechanical tests. Interactive personalized planning 520 may use feedback from biomechanical analysis 340 to further modify the personalized pre-surgical plan.

Biomechanical analysis tool 340 in FIG. 4 is one embodiment of an evaluation tool for evaluating the soundness of treatment plans generated by the system, including implant designs. The type of analysis employed by biomechanical analysis 340 may include orthopedic stress analysis of bone structures/prosthetic structures, orthopedic fixation devices, and other tissues. FIG. 7 illustrates an exemplary embodiment for biomechanical analysis 340 . Numerical analysis 610 functions may include finite element analysis (FEA), which evaluates the structural stability of the bone anatomy where the stress distribution is compared to the material properties of the bone, among other functions. Different numerical analysis methods are used to assess the structural integrity of orthopedic implants. For example, analysis of stress and displacement distributions of hip implants was used to assess the integrity of THR surgical planning. The analysis results of the numerical analysis 610 may be used to assist in surgical and non-surgical treatment of the patient. Numerical analysis model library 630 is a library that stores reference models (eg, FEA reference models) to provide real-time analysis and evaluation for pre-surgical planning and personalized implant design. Non-surgical treatment assessment 650 uses the assessment results to assist in non-surgical treatment planning. For example, based on the 3D model of the patient, the physician uses FEA analysis to assess the patient's condition, and decide on appropriate non-surgical treatment based on the results, and follow up before and after the treatment assessment with the post-treatment assessment 690 . For example, the FEA stress and displacement distribution in the necrotic region can be used to predict femoral head collapse in the early stages of osteonecrosis, and thus, it can be used to assist in non-surgical treatments such as drug therapy, joint weight reduction, mobility exercises and electrical stimulation. Pre-operative plan evaluation 670 provides interactive analysis to ensure the stability criteria of pre-operative plans from pre-operative plan 330 and reference models from numerical analysis model library 630, enabling real-time analysis and evaluation. For example, correct positioning of the acetabular cup ensures implant stability, as well as bearing surface wear and longevity. Post-Treatment Evaluation 690 provides pre-treatment and post-treatment evaluations for both non-surgical and surgical treatments. This is to provide an assessment for follow-up to monitor the progress of treatment results.

The analysis module of the present invention may include implant design tools for designing 3D models of personalized implants and surgical accessories such as guide plates. Personalization tool 350 in FIG. 4 is one form of embodiment of a personalized implant design tool. For convenience, and unless otherwise stated, the term "implant" is used broadly throughout the written specification and claims of this patent to encompass implants, molds for implants, molds for implants, Surgical accessories, such as guide plates, and molds for such surgical accessories.

Based on biomechanical simulations and testing, the evaluation tools discussed above can be used to evaluate implant models designed by implant design tools to ensure that the evaluation tools meet implant qualification requirements. Evaluation results for the implant model can be fed back to the implant design tool to improve the implant model. The biomechanical analysis tool also serves as an assessment of the requirements qualification process for individualized implant design to meet the required standards of the implant.

FIG. 8 illustrates some example components of personalization 350 . Personalize 350 to design a personalized implant model by modeling the 160 generated 3D model. Personalization 350 may include standard implant selection 710 , personalized implant design 730 , personalized qualification process 750 , custom/personalized implant model 770 and custom/personalized guide plate model 790 . Standard implant selection 710 uses the patient specific 3D model to select the closest matching standard implant model. Then, the physician user of the system checks the standard implant model using the personalized implant design 730, and edits the standard implant model if necessary, to generate an accurate and individualized implant model for the patient . Custom/Personalized Implant Model 770 generates a custom/personalized implant model and/or mold thereof for 3D printing. Customized/personalized guide plate model 790 allows a user to create a guide plate model (or a mold thereof) for 3D printing that will be used during a surgical procedure.

In a specific embodiment, the process for generating custom/personalized implant models includes the following steps: based on the type of surgery, standard implant selection 710 automatically selects the closest matching standard implant; providing a Group editing tools to modify the standard implant so as to generate a customized/individualized implant model that best fits the specific patient's 3D model via individualized implant design 730; Customized/personalized implant models for implant requirements. Based on test results generated from testing, such as biomechanical testing or other required testing, the qualification process can generate modification recommendations for personalized implant design. Personalized implant design 730 may use feedback from test results to further modify the personalized implant design. Examples of implants include, for example, joint surgery implants, prostheses, pins, rods, screws and plates.

In another embodiment, the process for generating a custom/personalized guide plate model comprises the steps of: selecting an ROI for the surgical procedure; automatically generating a 3D template model from the patient's 3D model; providing a set of editing tools to Pre-operative planning 330 Pre-operative planning incorporated into 3D template to generate custom/personalized guide plate via personalized implant design 730; customized/personalized guide plate model meeting stability requirements verified through personalized qualification process 750 . For convenience, and unless otherwise stated, when the patent uses the word "personalized" to refer to a 3D model, implant model, or treatment plan, it means that such 3D model, implant model, or treatment plan is created using the patient's own A custom designed for a patient based on radiographic images and other relevant information. Based on test results generated by testing, such as biomechanical testing or other required testing, the qualification process can generate recommendations for modifications to the personalized guide plate design. The personalized implant design 730 can use the feedback from the test results to further modify the personalized guide plate design. An example of a guide plate includes a guide plate for pedicle screw placement, where the position and angle of the screw is derived from the pre-surgical plan 330 .

3D printing module 360 is one embodiment of a physical building tool responsible for building a physical model corresponding to the virtual model generated by personalization 350 . Figure 9 illustrates exemplary components for 3D printing 360, wherein a 3D printer is used to produce a custom/personalized implant 810, a custom/personalized implant mold 830 for use before, during or after treatment , custom/personalized deflector mold 850 and/or 3D model mold 870. Other embodiments for physically constructing functions may include computerized numerical control (CNC) machining and injection molding.

FIG. 10 illustrates various embodiments of 2D, 3D output 180 . 2D 181 provides output in digital 182 form and/or hard copy 183 . 3D 184 includes, but is not limited to: 3D display with/without 3D glasses 185, Google Glass 186, virtual display 187, tactile display 188, and 3D printed models 189. 2D and 3D output can be displayed on hardware including But not limited to: monitor display 190, tablet/phone 191, smart device 192. 3D glasses 185 and Google Glass 186 are just examples of wearable technologies that can be deployed for display modules of the present invention.

Figure 11 illustrates the overall operation of the system according to one embodiment of the present invention. It begins with the physician selecting a particular disease from the user selection thread 170 . The physician ensures the accuracy of the 3D model through interactive visualization 320 and prints 3D model molds 870 if necessary. Diagnosis is performed via diagnosis 310 and/or combined with 3D model mold 870 for treatment planning. It exemplifies how the system decides whether surgery is required based on different stages of diagnosis. For the early stages - stage 1 910, stage 2 915 and some stage 3 920 that do not require surgery, the system further analyzes the situation using biomechanical analysis 340 and the physician can propose targeted treatment 935 and follow up with treatment based on the assessment. Enter 940 to follow up. There can be several follow-ups before treatment is complete. When surgery is required, the physician utilizes pre-surgical planning 330 for pre-surgical planning and personalization 350 for individualized implants and/or individualized guide plates followed by biomechanical analysis 340 based on user Specific criteria to assess the fit of the implant. The 3D printing 360 mechanism utilizes the personalized model from personalization 350 for printing custom/personalized implants 810 and/or custom/personalized guide plate molds 850 necessary for surgery 945 . Post-surgical follow-up 950 may involve assessment using biomechanical analysis 340 . If revision surgery is required after the post-surgical follow-up 950, the procedure is repeated again.

The foregoing descriptions are merely exemplary embodiments of the present invention. All the functional modules described above can be implemented by commonly utilized software technology or hardware technology or a combination thereof within the knowledge of a person of ordinary skill in the art.

Claims (33)

1. A system for planning orthopedic treatment comprising: a. a modeling module, based on radiographic images of a patient's body segment, which builds a treatment-relevant 3D model of said body segment; and b. An analysis module, including the following predefined analysis tools: i. an interactive visualization tool that allows a user of the system to visualize and edit said 3D model, ii. a quantification tool for obtaining measurements of said 3D model relevant to the treatment, iii. a planning tool for generating a surgical plan in view of said measurements and other relevant information of the patient, and iv. An evaluation tool for evaluating the surgical plan using biomechanical analysis; Wherein the planning tool allows the surgical plan to be modified using the output of the evaluation tool. 2. The system according to claim 1, wherein the analysis module also includes an implant design tool for generating an implant model in view of the measurement, and wherein the evaluation tool also allows the implant to be evaluated using biomechanical analysis The implant model, and the planning tool also allows the implant model to be modified using the output of the evaluation tool. 3. The system of claim 2, wherein the assessment tool further allows one or both of the following functions: non-surgical treatment assessment and post-treatment assessment. 4. The system according to claim 2, wherein the analysis module further comprises one or both of the following analysis tools: i. a diagnostic tool that, based on said radiographic image, gives an orthopedic diagnosis according to predefined criteria, ii. A construction tool that allows the construction of a physical object based on a model. 5. The system according to claim 4, further comprising a disease module containing a plurality of predefined workflows designated for specific orthopedic diseases, the disease module allowing the user to select a disease, automatically calling the A predefined workflow of one or more of said analysis tools in an appropriate sequence for treatment planning of a disease. 6. The system of claim 1, wherein the surgical plan can also be manually modified by user input. 7. The system of claim 2, wherein the implant model is also manually modifiable by user input. 8. The system of claim 1, further comprising an acquisition module that acquires the radiographic images by an image acquisition device or by retrieving images from a patient database. 9. The system of claim 1, wherein the modeling module allows for storage of a 3D model for a patient into a patient database and also allows retrieval of a 3D model from said patient database. 10. The system of claim 1, further comprising a correlation input module that retrieves relevant patient information from a patient database to be used by the analysis module. 11. The system of claim 5, further comprising a reporting module that generates reports based on results of operation of the system. 12. A system for planning orthopedic implant surgery on a patient, comprising: a. an implant design module for generating an implant model given a 3D model of the relevant orthopedic structure of the patient, and b. an evaluation module for evaluating the implant model using biomechanical analysis methods, Wherein the results of the evaluation module are sent back to the modeling module to improve the implant model. 13. The system of claim 12, further comprising a surgical planning module that generates a pre-surgical plan for implant surgery in view of the 3D model and patient-related information. 14. The system of claim 13, wherein the evaluation module further allows evaluation of the pre-surgical plan, and the surgical design module further allows modification of the pre-surgical plan using results of the evaluation module. 15. The system of claim 12, further comprising a building block that allows the implant model to be used to build an implant. 16. The system of claim 12, wherein the implant design module generates the implant model in view of quantitative measurements of the 3D model. 17. The system of claim 12, wherein the evaluation module includes a library of numerical analysis models enabling numerical evaluation of the implant model. 18. A system for planning orthopedic treatment comprising: a. An analysis module comprising two or more of the following analysis tools: i. an interactive visualization tool that allows a user of the system to visualize and edit a 3D model of a patient's orthopedic structure, ii. A quantification tool to obtain measurements of the 3D model, iii. A planning tool to generate a personalized surgical plan, iv. an evaluation tool for evaluating the surgical plan using biomechanical analysis, v. An implant design tool for generating personalized implant models, and vi. An evaluation module for evaluating implant models using biomechanical analysis; b. A disease module that allows a user to select a disease, automatically invoking a predefined workflow corresponding to said disease containing one or more of said analysis tools in an appropriate order. 19. The system of claim 18, wherein the analysis module further comprises a construction tool that allows construction of a physical object from a 3D model or an implant model. 20. The system of claim 19, further comprising a reporting tool that can be automatically invoked as part of a predefined workflow. 21. A method for computer planning orthopedic treatment of a patient comprising: a. acquiring two or more treatment-related radiographic images of a body segment of the patient, b. Conduct two or more of the following analyses: i. Diagnosis using said images with the aid of a computer system, ii. constructing a 3D model of the relevant orthopedic structure using said image, iii. measuring therapeutically relevant quantitative data from said 3D model; iv. generating a treatment plan in light of said quantitative data; v. Evaluate the treatment plan using biomechanical analysis; and vi. modifying said treatment plan using data from biomedical analysis; c. Report the results of the analysis. 22. The method of claim 21, wherein acquiring a radiographic image retrieves the image from a patient database. 23. The method of claim 21, further comprising obtaining relevant patient information and using said relevant patient information in one or more of said analyses. 24. The method of claim 21, wherein said analysis further comprises the following: i. Generate implant models using patient information and treatment requirements; ii. Evaluate the implant model using biomechanical analysis; iii. modifying the implant model using the output of said biomechanical analysis; and iv. Construct the implant using the implant model. 25. The method of claim 24, wherein said analyzing further comprises using said radiographic images for orthopedic diagnosis. 26. The method of claim 25, further comprising invoking a predefined workflow that automatically selects two or more of said analyzes in an order appropriate for treatment. 27. A method for computer planning orthopedic implant surgery of a patient comprising: a. using the radiographic images of the orthopedic structures to construct a 3D model of the relevant orthopedic structures for the patient, b. Given the 3D model an implant model is generated, c. Generate a treatment plan given the implant model, d. Evaluate the treatment plan using biomechanical analysis, and e. Modifying the treatment plan using data from said biomedical analysis. 28. The method according to claim 27, wherein the step of generating a treatment plan also includes generating a pre-surgical plan in view of the 3D model, the implant model and other relevant information of the patient, the step of evaluating the treatment plan further comprising evaluating the pre-surgical plan using a biomechanical analysis, and modifying the treatment plan further comprises modifying the pre-surgical plan using data from said biomedical analysis, a. Generate an implant model, b. Evaluate the implant model using biomechanical analysis, c. Modifying the implant model using the output of the biomedical analysis. 29. The method of claim 27, further comprising: a. Construct an implant using the implant model, b. Report the results of the treatment plan. 30. The method of claim 29, further comprising: a. Obtaining a second set of radiographic images of the body segment following the surgical procedure, b. constructing a second 3D model of the relevant orthopedic structure using said second set of radiographic images, c. Assessing the condition of the orthopedic structure by examining said second set of radiographic images and said second 3D model. 31. A system for computer-aided diagnosis of an orthopedic disorder in a patient, comprising: a. an acquisition module for acquiring disease-related radiographic images of a patient, b. a detection module for using an artificial intelligence algorithm to detect salient regions of the patient's relevant bony structure, and c. An analysis module for extracting bone features associated with orthopedic disease from said salient regions. 32. A system for planning orthopedic treatment of a patient comprising: a. a personalization module that allows the generation of a personalized 3D model or a personalized implant model, b. an evaluation module for evaluating the 3D model or the implant model using biomechanical analysis, wherein the personalization module can use the results of the evaluation module to modify the 3D model or the implant model, and c. An output module for displaying the results of the personalization module and the evaluation module. 33. The system of claim 32, wherein the output module utilizes a wearable display.