Shape-Based Anatomical Tree Segmentation for Reconnecting Branches
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Solution Overview
Problem
Existing minimally invasive medical techniques face challenges in accurately generating anatomical tree structures due to insufficient image segmentation, particularly in noisy data sets, leading to disconnected branched structures that hinder precise navigation and intervention.
Innovation Solution
A system and method for anatomical image data processing that assesses the shape and relationship between trunk and branched structures to determine connectivity, allowing for user-driven or automated connection of branched structures to the trunk, with visual differentiation and user interface controls for editing connections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated image segmentation is performed on noisy anatomic data, then processing speed is improved, but segmentation accuracy deteriorates leading to disconnected structures
Solution Approach 1:
A connector structure is introduced as an intermediary element to bridge disconnected branched structures and the trunk structure. The connector is generated based on shape assessments and spatial relationships, serving as a mediating component that reconstructs the anatomical connectivity lost during automated segmentation of noisy data.
Solution Approach 2:
The system performs preliminary assessments of branched structure shapes and their relationships to the trunk structure before finalizing the anatomical model. This preliminary analysis enables the system to identify disconnected components and plan connector placement in advance, improving overall segmentation accuracy without requiring manual intervention during the reconstruction phase.
2Measurement precision
If manual editing of segmented structures is allowed, then segmentation accuracy is improved, but user time and operational complexity increase
Solution Approach 1:
The system provides self-service functionality by automatically generating connector structures based on predefined shape assessments and spatial relationship criteria. This automation enables the system to correct segmentation errors independently, improving accuracy without requiring manual user intervention, thus avoiding time loss while maintaining precision.
Solution Approach 2:
The system implements feedback mechanisms where the generated connector structures are evaluated based on their conformity to expected anatomical shapes and relationships. This feedback loop allows the system to automatically refine and adjust connections, improving segmentation accuracy through iterative self-correction rather than manual editing.
3Device complexity
If disconnected branched structures are left unconnected, then device complexity is reduced, but navigation precision deteriorates
Solution Approach 1:
The anatomical structure is segmented into distinct components (trunk structure, branched structures, and connector structures) that can be independently analyzed and evaluated. This segmentation allows the system to maintain manageable complexity while ensuring each component's connectivity is properly assessed and reconstructed, preserving navigation precision without excessive overall complexity.
Data Source
AI summary
A system comprises a display system and a control system communicatively coupled to the display system. The control system is configured to receive anatomic image data for an anatomic tree structure and generate an initial segmentation of the anatomic image data. The initial segmentation includes a trunk structure and a branched structure unconnected to the trunk structure. The control system is also configured to determine whether to connect the branched structure to the trunk structure based on an assessment of a shape of the branched structure and an assessment of a relationship between the trunk structure and the branched structure.