Ulcer Image Segmentation and Case Comparison for Prognosis
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Solution Overview
Problem
Existing ulcer evaluation methods require invasive contact and lack effective comparison with previous cases for accurate prognosis and treatment decision support, especially for diabetic ulcers, and often require specialized equipment not universally available.
Innovation Solution
A non-invasive imaging-based procedure using CNNs for tissue segmentation, Euclidean distance comparisons of global characteristics vectors, and patient data integration to standardize ulcer analysis, enabling objective decision support and archiving for personalized treatment recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional contact-based ulcer evaluation methods are used, then direct assessment of ulcer characteristics is possible, but patient disruption and invasive contact are required
Solution Approach 1:
The patent replaces mechanical contact-based ulcer evaluation with optical imaging methods. A camera captures images of the ulcer, and image processing algorithms automatically measure ulcer area, tissue segmentation, and healing progression, eliminating the need for physical contact while maintaining assessment accuracy
Solution Approach 2:
The patent creates a digital copy of the ulcer through imaging. The captured images serve as representations of the ulcer's characteristics, allowing repeated measurements and comparisons without repeatedly contacting the patient's wound, thus avoiding disruption while maintaining measurement precision
2Ease of operation
If existing imaging methods are used to assess ulcer area reduction, then non-invasive evaluation is achieved, but tissue classification and prognostic support are insufficient
Solution Approach 1:
The patent segments the ulcer image into different tissue types (granulation tissue, slough, necrotic tissue, etc.) using image processing algorithms. This segmentation provides detailed tissue classification information while maintaining non-invasive evaluation, allowing the system to distinguish between different tissue states and their healing potentials
Solution Approach 2:
The patent adds multiple analytical dimensions to the basic area measurement. Instead of only measuring total ulcer area reduction, the system analyzes tissue composition, border characteristics, base characteristics, and healing patterns across multiple parameters, providing comprehensive prognostic information while remaining non-invasive
3Measurement precision
If specialized imaging equipment is used for ulcer analysis, then accurate imaging is achieved, but device availability is limited
Solution Approach 1:
The patent employs a low-cost camera instead of expensive specialized imaging equipment. The camera can be easily obtained and replaced, making the system widely accessible to different healthcare settings without requiring investment in costly specialized devices while maintaining adequate imaging accuracy for ulcer assessment
Solution Approach 2:
The patent makes the imaging system universal by using a standard camera that can be used across different healthcare settings, home care, and telemedicine. The same camera and software system can evaluate various ulcer types and stages, providing versatile functionality without requiring specialized equipment for different assessment scenarios
4Loss of time
If ulcer images from the same wound in different phases are compared, then healing progression is assessed, but prediction of evolution and risk assignment are limited
Solution Approach 1:
The patent implements feedback by comparing current ulcer images with previously recorded images from the same wound. The system automatically measures changes in area, tissue composition, and healing patterns over time, providing feedback on healing progression and enabling prediction of future evolution based on observed trends
Solution Approach 2:
The patent performs preliminary analysis by establishing baseline characteristics and risk factors at the initial assessment. The system records patient-specific parameters, ulcer location, and initial tissue composition to create a reference profile that enables future comparisons and prognostic predictions, preparing the necessary data structure before healing begins
Data Source
AI summary
An ulcer-related control, prognosis and comparative support procedure is provided that includes the following stages: measuring the area of the ulcer and ROI (1) by taking an image of the area of the ulcer and ROI (1.a), segmenting the tissues obtained in the image of the ulcer area and ROI (1.a)., obtaining the base characteristics vector, depicting the state of the tissues, classifying ulcers, supporting user's decisions, archiving registered clinical cases, and supporting user's decisions by comparing the global characteristics vector with the global characteristics vectors of the registered ulcer clinical cases.