Progressive Anatomical Point Registration Against False Local Minima
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Solution Overview
Problem
Existing minimally invasive medical techniques face challenges in accurately registering medical tools with images of anatomic passageways due to the likelihood of converging to false local minima during iterative registration, especially in complex and deformable branched structures.
Innovation Solution
A progressive iterative point matching technique that initially anchors registration around more stable anatomical areas and progressively expands to more complex regions, using rigid and non-rigid transforms, and introduces noise to reduce false minima.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If iterative registration is used to align medical tools with anatomic images, then registration can be performed automatically, but the system may converge to false local minima reducing accuracy
Solution Approach 1:
The patent segments the anatomic structure into multiple hierarchical levels or regions, performing registration iteratively at each level before proceeding to the next. This breakdown of the global registration problem into smaller local registration tasks prevents convergence to false local minima by establishing correct alignment at each hierarchical stage, thereby maintaining both automation and accuracy.
2Adaptability or versatility
If registration is performed in complex and deformable branched structures, then comprehensive coverage is achieved, but the likelihood of converging to false local minima increases
Solution Approach 1:
The patent divides complex branched structures into manageable segments or hierarchical levels, registering each segment separately before integrating results. This approach maintains accuracy in complex deformable structures by preventing global optimization from being trapped in local minima, while still achieving comprehensive coverage of the entire structure.
Solution Approach 2:
The patent performs preliminary registration at coarser hierarchical levels before refining at finer levels. This preliminary action establishes a good initial alignment that guides subsequent detailed registration, reducing the risk of converging to false local minima in complex deformable structures while maintaining comprehensive coverage.
3Measurement precision
If more transformation iterations are performed to improve alignment, then registration precision increases, but computational time increases
Solution Approach 1:
The patent segments the registration process into hierarchical levels, performing transformations at each level before proceeding to the next. This segmentation allows the system to achieve high overall precision through multiple transformation stages without requiring an excessive number of iterations at any single level, thus balancing precision with computational efficiency.
Data Source
AI summary
A system receives a first set of points corresponding to an anatomical feature. Each point in the first set of points represents a position in a first frame. The system receives a second set of points corresponding to the anatomical feature. Each point in the second set of points represents a position in a second frame. The system identifies a first subset of the first set of points and determines a first transformation to align the first subset of the first set of points with the second set of points. The first set of points is transformed based on the first transformation. The system identifies a second subset of the first set of points and determines a second transformation to align the first and second subsets of the first set of points with the second set of points. The first set of points are transformed based on the second transformation.