Smartphone Skin Analysis Using Color Calibration Chart
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Solution Overview
Problem
Smartphones lack uniformity in image capture capabilities, making them unsuitable for regulatory-approved medical examinations due to variations in camera settings and illumination conditions, and are often operated by unqualified users who may not follow strict medical procedures.
Innovation Solution
A system that uses a mobile communications device to capture and analyze images of skin features, employing a colorized surface for image calibration to correct for local illumination and capturing parameters, allowing for accurate determination of skin conditions over time, and providing recommendations for medical actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If smartphones are used for medical examination of skin features, then accessibility and ease of operation are improved, but image quality uniformity and measurement precision deteriorate due to variations in camera settings and illumination conditions
Solution Approach 1:
The system changes the parameter of illumination by using a controlled light source with specific spectral characteristics to illuminate the skin feature. This standardized illumination parameter compensates for the variability in ambient lighting conditions when using smartphones, thereby maintaining measurement precision while preserving ease of operation.
Solution Approach 2:
The system introduces an intermediary color calibration chart between the smartphone camera and the skin feature. This intermediary object serves as a reference for color accuracy, allowing the system to correct for variations in camera settings and illumination conditions, thus maintaining measurement precision while using accessible smartphone devices.
2Measurement precision
If dedicated hardware scanners with pre-calibrated systems are used, then measurement precision and reliability are improved, but device complexity and cost increase
Solution Approach 1:
The system extracts only the essential calibration and measurement functions from complex dedicated hardware scanners. By using a simple smartphone camera combined with a color calibration chart and controlled illumination, the system achieves measurement precision without requiring the complex pre-calibrated scanner hardware, thereby reducing device complexity while maintaining accuracy.
3Reliability
If multiple images are captured over time to monitor skin feature changes, then diagnostic accuracy is improved, but loss of time and processing complexity increase
Solution Approach 1:
The system implements automated feedback through machine learning algorithms that analyze multiple images captured over time. The system automatically compares skin feature changes across images, provides real-time feedback on healing progress or condition changes, and generates diagnostic recommendations. This automated feedback loop improves diagnostic accuracy while minimizing time loss by eliminating manual analysis delays.
Data Source
AI summary
Systems and methods for image processing of a skin feature may include receiving from at least one image sensor associated with a mobile communications device a first and a second images of a skin feature. The skin feature has multiple segments of differing colors and differing sizes, and the second image is captured at least a day after the first image is captured. The method may further include analyzing data associated with the first and second images to determine a condition of the skin feature based on changes over time of the multiple segments. The method may also include determining, based on the determined condition of the skin feature, a medical action for treating the skin feature during a time period. Then, the method may include causing a mobile communications device to display information indicative of the determined medical action.