Medical Image Editing with Auto-Snapping Vertex Ranking
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Solution Overview
Problem
Medical image editing, particularly for low-contrast and noisy images, is tedious and inefficient due to the difficulty in accurately identifying and manipulating vertices in 3D surface models, especially when occlusion occurs in 3D mesh viewers or vertices are not visible in the current viewing plane.
Innovation Solution
A medical image editing device and method that assigns ranking values to vertices based on proximity and anatomical significance, allowing users to easily identify and modify intended vertices for editing, even when occluded, by combining 3D surface models with 2D medical images and using auto-snapping features to facilitate precise interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual vertex selection is used in 3D mesh viewers, then users can interact with vertices, but the process becomes tedious and time-consuming when vertices are occluded or not visible in the current viewing plane
Solution Approach 1:
The patent introduces an intermediary mechanism (auto-snap function with ranking values) that mediates between the user's point-of-interest input and the actual vertex selection. The system automatically identifies the intended vertex based on proximity and anatomical significance, eliminating the need for direct manual vertex picking in occluded or difficult-to-see scenarios.
Solution Approach 2:
The system performs self-service by automatically determining which vertex the user intends to edit based on the point-of-interest and ranking values. The auto-snap function serves itself by autonomously selecting the appropriate vertex without requiring continuous manual intervention, thus reducing the operational burden on the user.
2Measurement precision
If ranking values are assigned to vertices based on proximity and anatomical significance, then vertex identification accuracy improves, but the system complexity increases
Solution Approach 1:
The patent applies local quality by assigning different ranking values to different vertices based on their specific properties (proximity to point of interest, anatomical significance, curvature, junction status). Each vertex has a customized ranking that reflects its local characteristics, enabling precise identification without requiring complex global analysis of the entire mesh.
Solution Approach 2:
The system uses parameter changes by varying the ranking values based on multiple criteria (proximity distance, anatomical meaning, curvature degree). This allows the system to dynamically adjust vertex priorities based on the current context and user input, improving identification accuracy through parameter-based differentiation rather than complex structural changes.
3Shape
If 3D surface models are used for medical image editing, then spatial representation is improved, but visibility of vertices is reduced due to occlusion in 3D mesh viewers
Solution Approach 1:
The patent uses an intermediary approach by introducing ranking values and auto-snap functionality as a mediator between the 3D visual representation and the vertex selection process. This intermediary layer compensates for the visibility problems in 3D mesh viewers by providing alternative means of vertex identification that do not depend on direct visual access to the vertex in the 3D display.
Solution Approach 2:
The system addresses the visibility issue by operating in another dimension - using proximity calculations and anatomical metadata rather than relying solely on 3D visual visibility. The auto-snap function evaluates vertices based on their spatial relationship to the point of interest and their anatomical properties, effectively moving the selection criterion from visual perception to computational assessment.
Data Source
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AI summary
The present invention relates to medical image editing. In order to facilitate the medical image editing process, a medical image editing device (50) is provided that comprises a processor unit (52), an output unit (54), and an interface unit (56). The processor unit (52) is configured to provide a 3D surface model of an anatomical structure of an object of interest. The 3D surface model comprises a plurality of surface sub-portions. The surface sub-portions each comprise a number of vertices, and each vertex is assigned by a ranking value. The processor unit (52) is further configured to identify at least one vertex of vertices adjacent to the determined point of interest as an intended vertex. The identification is based on a function of a detected proximity distance to the point of interest and the assigned ranking value. The output unit (54) is configured to provide a visual presentation of the 3D surface model. The interface unit (56) is configured to determine a point of interest in the visual presentation of the 3D surface model by interaction of a user. The interface unit 56 is further configured to modify the 3D surface model by displacing the intended vertex by manual user interaction. In an example, the output unit (54) is a display configured to display the 3D surface model directly to the user (58).