Remote Varicose Vein Risk Assessment Using Capillary Digitization
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Solution Overview
Problem
There is a need for an effective method to diagnose and manage varicose veins early to reduce the incidence and associated social costs, particularly through a non-face-to-face service platform.
Innovation Solution
A method involving a server that acquires varicose veins-related information from a user device, digitizes capillary exposure, evaluates the risk based on analysis, and transmits evaluation results, utilizing image and video analysis, user questionnaire data, and wearable device information to provide non-face-to-face diagnosis and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a non-face-to-face service platform is used for varicose veins diagnosis, then convenience and accessibility are improved, but diagnostic accuracy and reliability may deteriorate
Solution Approach 1:
The patent introduces an AI-based image analysis system as an intermediary between the patient and the final diagnosis. The system processes images captured by user devices, automatically detects capillary exposure patterns, and generates preliminary diagnosis results. This intermediary maintains diagnostic accuracy by using standardized algorithms while enabling remote, convenient access without requiring direct patient-physician interaction for image capture.
Solution Approach 2:
The patent replaces the mechanical/physical examination process with automated image analysis. Instead of requiring a physician to physically examine the patient's veins, the system uses computer vision algorithms to analyze images of the affected area, detect capillary patterns, and assess varicose veins risk. This substitution maintains diagnostic reliability through algorithmic consistency while dramatically improving convenience and accessibility.
2Measurement precision
If multiple data sources (images, videos, questionnaire data, wearable device information) are integrated for diagnosis, then diagnostic accuracy is improved, but system complexity increases
Solution Approach 1:
The patent merges multiple data sources (images, videos, questionnaire responses, and wearable device data) into a unified diagnostic framework. The AI system integrates these diverse inputs to comprehensively assess capillary exposure patterns and varicose veins risk. This merging approach improves diagnostic accuracy by considering multiple aspects of the condition while managing complexity through centralized processing architecture.
Solution Approach 2:
The patent creates a multi-functional diagnostic platform that can process various types of data (visual images, video sequences, text questionnaires, and sensor data) through a single AI system. This universal system performs multiple functions including image analysis, pattern recognition, risk assessment, and diagnosis generation, thereby improving accuracy through comprehensive evaluation while avoiding the complexity of separate specialized systems for each data type.
3Measurement precision
If capillary exposure is digitized through detailed image analysis, then measurement precision is improved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary processing of images to identify and segment the relevant anatomical regions before conducting detailed capillary exposure analysis. The system pre-processes images to enhance relevant features, crop to areas of interest, and prepare data structures that facilitate faster subsequent analysis. This preliminary action maintains measurement precision by ensuring thorough analysis of critical areas while reducing overall processing time by avoiding exhaustive analysis of entire images.
Solution Approach 2:
The patent applies partial action by focusing detailed analysis only on specific regions where capillary exposure is most relevant to varicose veins diagnosis, rather than analyzing entire images in equal detail. The system identifies key anatomical zones and concentrates computational resources on these areas, thereby achieving sufficient measurement precision for clinical decision-making while significantly reducing processing time and computational requirements compared to exhaustive full-image analysis.
Data Source
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AI summary
Examples relate to a method for early diagnosis and management of varicose veins by a server, comprising acquiring varicose veins-related information from a user device, digitizing a capillary exposure based on analysis of the varicose veins-related information, evaluating a risk of varicose veins based on the digitized capillary exposure, and transmitting information of varicose veins evaluation results based on the evaluated risk of varicose veins to the user device.