Automated Hinge Detection for Orthopedic Fixators
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Solution Overview
Problem
Conventional techniques for controlling orthopedic fixator manipulation are inefficient and unreliable due to difficulties in identifying and marking fixator elements like hinges in radiographic images, leading to errors and compromised alignment of anatomical structures during the healing process.
Innovation Solution
An automated or semi-automated hinge detection process using computer software to analyze images and identify hinge locations, employing circle detection algorithms and image analysis techniques to determine the spatial relationship between image planes and calculate adjusted hinge locations for accurate manipulation of the fixation apparatus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a surgeon or user manually indicates locations of fixator elements in radiographic images, then the treatment plan can be developed, but the process becomes time-consuming and error-prone due to difficulty in identifying hinges and other elements
Solution Approach 1:
The patent replaces the manual mechanical process of visually searching and marking hinge locations with an automated computer vision system. The system uses image processing algorithms to automatically detect, identify, and mark the locations of hinges and other fixator elements in radiographic images, eliminating the time-consuming and error-prone manual process while maintaining or improving accuracy.
Solution Approach 2:
The system enables self-service by allowing the computer to automatically perform the task of identifying and marking fixator elements without requiring surgeon intervention. The automated detection system independently analyzes the radiographic images, locates hinges based on their geometric characteristics, and provides the results directly for treatment planning, making the process more efficient and reliable.
2Loss of information
If hinges and fixator elements are captured from certain orientations, then complete anatomical coverage is achieved, but the elements become obscured or overlapping making identification difficult
Solution Approach 1:
The patent addresses the visibility problem by analyzing multiple radiographic images taken from different orientations and projections. The system integrates information across multiple dimensional views to reconstruct the three-dimensional positions of hinges, allowing elements that may be obscured in one view to be identified from other angles, thereby recovering complete anatomical information without being limited by single-view obscuration.
Solution Approach 2:
The system introduces an intermediate computational processing layer that bridges the gap between obscured visual information and accurate hinge location identification. The image processing algorithms act as intermediaries that analyze geometric patterns, contextual relationships, and spatial configurations across multiple images to deduce hinge locations even when direct visual identification is difficult, thereby resolving the contradiction between image complexity and information recovery.
3Ease of manufacture
If manual identification of fixator elements is used, then the process is simple to implement, but errors increase and reliability of treatment plan decreases
Solution Approach 1:
The patent replaces the simple but unreliable manual marking process with an automated computer vision system that uses image processing algorithms to detect and identify hinges. This substitution maintains ease of implementation from the user perspective while dramatically improving reliability, as the automated system consistently identifies hinge locations based on objective geometric criteria rather than subjective human judgment.
Solution Approach 2:
The system incorporates feedback mechanisms where the computer automatically validates detected hinge locations by analyzing geometric consistency, spatial relationships, and contextual information from multiple images. This feedback loop ensures high reliability by cross-verifying detections and correcting potential errors, while the automated nature maintains ease of implementation without requiring complex manual verification procedures.
Data Source
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Figure 3A
AI summary
First and second images are displayed of anatomical structure segments with an attached fixator. Indications may be received of first image hinge locations of a plurality of hinges of the fixator in the first image. Projected second image hinge locations may be determined based at least in part on the first image hinge locations. Hinge candidates may be detected in the second image having shapes associated with the plurality of hinges. The hinges candidates may be detected by computer software using automated software-based image analysis techniques. Adjusted second image hinge locations may then be calculated based at least in part on the projected second image hinge locations and candidate second image hinge locations. The adjusted second image hinge locations may be used to determine physical locations of the fixator and anatomical structure segments in three-dimensional space, which may be used to determine manipulations to the fixator for deformity correction.