Semi-Automated MAR Analysis System for Cervical Spine
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Solution Overview
Problem
The existing methods for determining the Mean Axis of Rotation (MAR) of the spinal vertebrae are time-consuming and prone to errors due to their manual and semi-automated nature, requiring substantial effort and lacking precision in data collection and analysis.
Innovation Solution
A semi-automated method utilizing computer vision techniques to reduce the time and effort required for MAR analysis, allowing user intervention for accuracy, and storing data as double precision numbers for enhanced precision, with features like auto-adjustment for inter-user differences and smooth tracing without the need for numerous clicks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracing methods are used to determine MAR, then measurement precision can be maintained through careful observation, but the time required increases significantly to 140 minutes
Solution Approach 1:
The patent replaces manual mechanical tracing operations with computer vision algorithms and automated image processing systems. The computer automatically detects vertebral landmarks, traces vertebral bodies, and calculates MAR positions through programmed algorithms, substituting human manual operations with automated computational processes that achieve both speed and precision
Solution Approach 2:
The system enables self-service by allowing the computer to automatically perform trace verification, error detection, and quality control checks without requiring constant human intervention. The automated system validates its own results and can correct certain types of errors independently, reducing the time experts need to spend on verification
2Ease of operation
If semi-automated methods with numerous clicks are used for tracing, then ease of operation improves, but measurement precision deteriorates due to rounding errors from integer coordinates
Solution Approach 1:
The patent changes the data representation parameter from integer coordinates to double-precision floating-point numbers. This parameter change allows the system to maintain high measurement precision while working with automated tracing methods, eliminating the rounding errors that occur with integer-based coordinate systems
Solution Approach 2:
The system replaces manual click-based tracing with automated computer vision algorithms that can determine sub-pixel precision landmark locations. This substitution eliminates the need for users to manually click on images, providing both ease of operation and high precision through algorithmic coordinate determination
3Productivity
If fully automated computer vision methods are implemented, then productivity increases significantly, but device complexity increases due to advanced image processing requirements
Solution Approach 1:
The patent segments the complex image processing task into distinct modular components: pre-processing module for image enhancement, landmark detection module for identifying key points, vertebral tracing module for outlining vertebral bodies, and MAR calculation module for computing rotation axes. This segmentation reduces overall system complexity by making each component independent and manageable
Solution Approach 2:
The system performs preliminary actions by automatically pre-processing images to enhance contrast and sharpness before main analysis, and by automatically detecting and marking vertebral landmarks before full tracing. These preliminary automated steps reduce the complexity of subsequent processing stages and improve overall productivity
4Measurement precision
If stricter criteria for recognizing vertebral landmarks are applied, then measurement precision improves, but ease of operation worsens due to increased difficulty in identifying landmarks
Solution Approach 1:
The patent replaces manual landmark identification with automated computer vision algorithms that use image processing techniques to detect and verify vertebral landmarks. This substitution maintains high measurement precision through strict computational criteria while dramatically improving ease of operation, as the computer performs the difficult identification task automatically
Solution Approach 2:
The system implements feedback mechanisms where the automated landmark detection provides suggestions to users, and users can verify or correct these suggestions. The system also provides feedback on the quality of detected landmarks and adjusts its detection parameters based on verification results, improving both precision and ease of operation through iterative refinement
Data Source
AI summary
A computer readable storage medium for determining a normalized mean axis of rotation (MAR) of a cervical spine in a patient is provided, having stored thereon instructions executable by a processor to perform steps of providing a flexion trace and an extension trace of each of cervical spine vertebrae C2 to C7 by detecting a start position, drawing a line concurrently as the pointing device follows the margin from the start position to a finish position and detecting the finish position; superimposing the flexion trace on the extension trace; providing for a user to correct an error in a trace; determining a MAR datum; and normalizing the MAR datum.