Wound Image Clarification via Lighting Normalization
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Solution Overview
Problem
Conventional in-home wound care methods rely on subjective assessments by caretakers, which can lead to missed diagnoses of worsening wound conditions due to varying experience levels and environmental challenges like inadequate lighting.
Innovation Solution
A mobile app and network service that captures wound images using a smartphone, normalizes them for lighting and angle variations, and analyzes them using trained models to provide an objective assessment and treatment recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If subjective assessment by caretakers is used for wound evaluation, then ease of operation is improved, but measurement precision deteriorates due to varying experience levels and environmental challenges
Solution Approach 1:
The patent uses smartphone cameras to capture visual copies of wound images, replacing the subjective visual assessment by caretakers with objective digital imaging. The smartphone camera serves as a standardized copying device that captures wound appearance consistently across different users and environments, eliminating the variability in human assessment while maintaining ease of operation through simple image capture.
Solution Approach 2:
The patent replaces the mechanical system of human visual inspection and manual evaluation with an automated image processing system. The smartphone camera captures images that are then processed by computer vision algorithms and machine learning models, substituting the caretaker's subjective judgment with automated computational analysis that provides consistent and precise measurements.
2Ease of operation
If ambient lighting conditions are used for wound imaging, then ease of operation is improved, but image quality deteriorates due to inadequate lighting
Solution Approach 1:
The patent converts the harmful effect of inadequate ambient lighting into a beneficial situation by using image processing algorithms that specifically address low-light conditions. The system detects poor lighting conditions and applies correction algorithms that enhance image quality, turning the limitation of ambient lighting into an opportunity to demonstrate the system's ability to compensate for environmental challenges and maintain accurate wound assessment.
Solution Approach 2:
The patent changes the parameters of the captured images through digital processing. When ambient lighting is insufficient, the system adjusts image parameters such as brightness, contrast, and exposure through computational algorithms, transforming the degraded image quality into acceptable or excellent quality while maintaining the ease of operation in ambient lighting conditions.
3Measurement precision
If multiple trained models are invoked for comprehensive wound assessment, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the wound assessment task into multiple specialized models, each responsible for evaluating specific aspects of wound health such as healing progress, infection indicators, and tissue characteristics. This segmentation allows the system to achieve high measurement precision through specialized analysis while managing complexity by dividing the overall assessment function into independent, manageable components that can be invoked selectively.
Solution Approach 2:
The patent creates a universal wound assessment system where multiple trained models work together to provide comprehensive evaluation. The system architecture is designed so that different models can be invoked based on the specific assessment needs, with a unified interface that manages the complexity of coordinating multiple specialized functions through a single multi-functional platform.
Data Source
AI summary
A wound care treatment platform and application employs a mobile device and application (“app”) for on-site capture and gathering of wound images from a patient. The mobile device is in wireless communication with a database including health records and data and trained models of wound image classification. Based on a patient image of a wound under care, the image is analyzed for features indicative of wound health and healing progress. The mobile device invokes a plurality of models for providing an accurate and consistent assessment and treatment recommendation, including evaluating the sufficiency of the patient image gathered by the mobile device, normalizing the patient image for adverse or irregular lighting, common in patient dwellings, adjusting for a distance and angle at which the caretaker obtained the image, computing a comprehensive score of wound healing, and rendering an evaluation for referral or continuance of current outpatient care.