Joint Space Quantification Using 3D Imaging and Neural Networks
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Solution Overview
Problem
Current medical imaging technologies provide subjective and qualitative assessments of joint spacing, limiting the accuracy and precision in diagnosing conditions affecting joint spacing, such as arthritis and ligament injuries, as they do not quantify bone distances effectively.
Innovation Solution
A joint space quantification system that identifies and measures bone distances in three-dimensional medical images, generating computer models and using neural networks to combine these measurements with biological and biomechanical data for precise condition diagnosis and severity assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If three-dimensional medical imaging technology (CT or MRI) is used to visualize joint spaces, then the visualization capability is improved, but the measurement precision of bone distances remains insufficient due to subjective assessment
Solution Approach 1:
The patent replaces the subjective human visual assessment system with an automated computer-based image processing and measurement system. The system automatically identifies bone structures, calculates joint space measurements, and generates quantitative reports, eliminating the subjectivity inherent in manual visual assessment while maintaining the three-dimensional visualization capabilities of CT and MRI imaging.
2Ease of operation
If subjective qualitative assessment methods are used for diagnosing joint spacing conditions, then the diagnostic process is simple, but the diagnostic accuracy and precision are limited
Solution Approach 1:
The system enables automated self-assessment of joint spacing conditions through computer-based image analysis. The software automatically processes medical images, identifies bone structures, measures joint spaces, and generates diagnostic reports without requiring manual measurement by practitioners, thereby maintaining operational simplicity while significantly improving measurement precision and diagnostic accuracy.
3Measurement precision
If automated image processing and measurement systems are implemented, then the measurement precision of bone distances is improved, but the system complexity increases
Solution Approach 1:
The patent implements a multi-functional integrated system that performs multiple tasks within a single software platform: three-dimensional reconstruction of bone structures, automatic bone identification and segmentation, joint space measurement and calculation, comparison with reference data, and generation of diagnostic reports. This consolidation of multiple functions into one system reduces operational complexity despite the advanced capabilities, making the sophisticated measurement system easier to deploy and use.
Data Source
AI summary
In order to more accurately and precisely diagnose conditions affecting joint spacing, a joint space quantification system is disclosed that identifies each bone in a three-dimensional medical image, generates a three-dimensional computer model that includes a three-dimensional representation of each bone, and identifies bone distances (e.g., shortest distances, centroid distances, etc.) between each three-dimensional representation. The joint space quantification system may then identify conditions affecting joint spacing (and quantify the severity of those conditions), for example by comparing the identified bone distances to previous bone distances of the patient and/or the bone distances of patients diagnosed with conditions affecting joint spacing. In some embodiments, the joint space quantification system also includes a neural network that combines those bone distances with biological, biomechanical, and/or performance data to generate a multivariate model for identifying, predicting, and/or avoiding those conditions affecting joint spacing.