Dermatological Lesion Tracking System with Composite Image Analysis
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Solution Overview
Problem
Current systems for tracking and monitoring skin lesions are physician-centric and require patients to visit a doctor's office, limiting their effectiveness for patients who cannot or do not keep yearly appointments, and lack the ability for remote self-photography and proper image analysis.
Innovation Solution
A computerized method and system that allows patients to use a client device with a camera to take and compare photographs of skin lesions using graphical templates, creating composite images to highlight changes, and linking diagnostic information with images for physician review, enabling remote monitoring and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If current physician-centric systems are used for tracking skin lesions, then dermatologists can monitor lesions during office visits, but patients must travel to the doctor's office which limits compliance and remote monitoring capability
Solution Approach 1:
The system enables patients to independently photograph and track their own skin lesions at home without requiring physician presence or office visits. Patients use their personal devices to capture images, which are then automatically uploaded and integrated into the medical record system, allowing self-service monitoring that improves compliance while eliminating travel requirements
Solution Approach 2:
The system works across multiple platforms including mobile devices, tablets, and computers, allowing patients to use whichever device is most convenient for them. The system integrates with existing electronic medical record infrastructure while providing standalone functionality, making it universally accessible regardless of the patient's specific device or location
2Extent of automation
If patients take self-photographs without guidance, then remote monitoring is enabled, but image quality and consistency are insufficient for accurate medical analysis
Solution Approach 1:
The system provides pre-configured photographic templates with marked anatomical landmarks and lesion locations that guide patients before they take images. These templates ensure proper framing, lighting, and positioning are established in advance, so patients know exactly how to capture medically useful images without requiring post-capture correction or retakes
Solution Approach 2:
The system replaces the need for manual image quality assessment and adjustment by using automated computer vision algorithms that analyze captured images for proper positioning, lighting, and focus. The system automatically requests retakes or adjustments when images do not meet quality thresholds, eliminating the need for mechanical intervention by physicians to correct poor-quality images
3Loss of information
If multiple detailed photographs are taken for each lesion, then comprehensive diagnostic information is captured, but the complexity of image management and analysis increases
Solution Approach 1:
The system automatically merges multiple photographs of the same lesion into a single composite image that preserves all diagnostic details from different angles and zoom levels. The composite maintains spatial relationships between lesions and anatomical landmarks while integrating multiple views, allowing physicians to review comprehensive information in a single organized display rather than navigating through numerous separate images
Solution Approach 2:
The system segments the image management process by automatically categorizing photographs into hierarchical groups based on anatomical location, lesion type, and temporal sequence. Each lesion is assigned a unique identifier that links all related images, and the system organizes them into structured folders with metadata, reducing management complexity through automated classification rather than requiring manual sorting of all images
4Measurement precision
If baseline and follow-up photographs are compared manually, then changes in lesions can be detected, but the process is time-consuming and prone to human error
Solution Approach 1:
The system replaces manual visual comparison with automated computer vision algorithms that objectively measure lesion characteristics including size, color, shape, and texture parameters. The algorithms quantitatively compare baseline and follow-up images, detecting changes with precision beyond human capability and flagging only those lesions that exceed predetermined thresholds for clinical significance, eliminating subjective bias and fatigue-related errors
Solution Approach 2:
The system provides automated feedback to physicians by highlighting only those lesions that show significant changes between visits, along with quantitative measurements and visual overlays showing the nature of changes. This feedback mechanism filters out stable lesions that require no action, allowing physicians to focus their attention on clinically relevant cases and reducing overall review time while maintaining detection sensitivity
Data Source
AI summary
A computerized method for recording and tracking dermatological lesions is disclosed. The method comprises creating a graphical template of a portion of a human form to assist in taking a photograph of the human body. A composite image of the template and video input are displayed to ensure accuracy of the image. The system also permits a user to highlight multiple dermatological lesions present on the body. When a user highlights the location of a lesion the system prompts the user to create an enhanced zoom image to capture details of the lesion. When multiple enhanced zoom images are created the system permits a user to create a merged image of multiple images of the lesion. The system aligns the images and creates visual accents to quickly display the differences between the photographs, allowing a user to quickly identify changes in the lesion over time.