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Updated: Jul 11, 2026
05:33
Three-Dimensional Shape Modeling and Analysis of Brain Structures
Published on: November 14, 2019
Topology-preserving contourwise shape fusion.
Aleksandra Melnikova1, Martin Maška2, Petr Matula2
1Masaryk University, Brno, Czech Republic. xmelnik@fi.muni.cz.
Scientific Reports
|March 29, 2025
Summary
We developed a novel shape fusion method that preserves complex shape features and topology. This shape-aware topology-preserving means (SATM) method reliably establishes consensus segmentation and computes accurate mean shapes.
Area of Science:
- Computer Vision
- Computational Geometry
- Image Analysis
Background:
- Preserving morphological features and topology is crucial for shape analysis.
- Existing fusion methods often smooth features or alter topology.
- Accurate shape representation is needed for benchmarking and consensus building.
Purpose of the Study:
- To introduce a novel contourwise topology-preserving fusion method.
- To compare the proposed method with state-of-the-art fusion techniques.
- To demonstrate the method's effectiveness in preserving shape complexity and topology.
Main Methods:
- Developed shape-aware topology-preserving means (SATM) for merging complex shapes.
- Employed key point matching and piecewise contour averaging.
- Focused on contourwise fusion to maintain topological integrity.
Main Results:
- SATM successfully preserves morphological features like protrusions and concavities.
- The method maintains the topology of input shapes without smoothing.
- Experiments show SATM outperforms existing techniques in shape-related measures.
Conclusions:
- SATM is a reliable method for establishing consensus segmentation annotations.
- The proposed technique accurately computes mean shapes while preserving complexity.
- SATM advances shape analysis by preserving critical geometric and topological information.
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