Skin Lesion Image Linking Using ID-Based Closeup Association
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems face challenges in organizing and linking close-up images of skin lesions to their corresponding features in a body model, especially when lesions change size, shape, or disappear over time, without the need for direct connection to the overview image.
Innovation Solution
A method and system that assigns an identifier (ID) to skin lesions in an overview image, communicates this ID to a mobile device, and links high-resolution close-up images of the lesions to the identified lesions in the overview image using codes or backend connections, allowing for convenient image association without direct connection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional image processing methods are used to identify and link closeup images with panoramic images, then the process requires significant manual intervention and computational resources, but the system becomes complex and time-consuming
Solution Approach 1:
A photo link database is introduced as an intermediary component that stores pre-established relationships between closeup image hashes and panoramic image metadata. The hashing module generates hashes that query this database, which returns pre-linked results without requiring complex real-time image analysis. This mediator eliminates the need for sophisticated image processing algorithms while maintaining accurate linking.
Solution Approach 2:
Instead of processing and comparing full image data, the system creates simplified copies in the form of hash values (e.g., SHA-256 hashes) that uniquely represent each closeup image. These hash copies are stored in the photo link database and used for rapid comparison and identification, replacing computationally intensive image matching operations.
2Measurement precision
If manual identification of closeup images is performed, then image matching can be achieved, but the process is time-consuming and reduces productivity
Solution Approach 1:
The manual mechanical process of image identification is replaced with an automated computational system. The hashing module automatically generates unique hash values for closeup images, and the photo link database automatically retrieves matching panoramic images based on these hashes. This substitution eliminates manual intervention entirely while maintaining identification accuracy and dramatically increasing processing speed.
Solution Approach 2:
The system performs preliminary actions by pre-processing closeup images into hash values and pre-establishing links in the photo link database before actual panorama creation is needed. This preliminary hashing and linking work is done once, allowing rapid retrieval and association during the actual panorama stitching process, thereby increasing overall productivity.
3Measurement precision
If sophisticated image processing algorithms are used to match closeup images with panoramas, then matching accuracy improves, but computational energy consumption increases
Solution Approach 1:
The system extracts only the essential identifying features from closeup images by converting them into hash values, discarding the rest of the image data. This extraction approach maintains matching precision by preserving unique identifiers while eliminating the need for energy-intensive processing of full image content. The photo link database stores only these compact hash representations for efficient querying.
Data Source
Figure 1~2
Figure 3~4
Figure 5~6
AI summary
The present disclosure relates to a method in a computer system (10) storing a model (1) of a body (B). The model comprises an overview image of a surface of skin of the body. The method comprises, in the overview image, identifying a lesion in the skin. The method also comprises assigning an ID to the identified lesion. The method also comprises communicating the ID to a mobile device (3). The method also comprises, at a data storage (2) of the computer system, receiving a closeup image of the lesion together with the communicated ID from the mobile device. The method also comprises, in said data storage, linking the received closeup image to the identified lesion in the overview image.