Shape bottlenecks and conservative flow systems [medical image analysis]
Abstract
Proposes an alternative to mathematical morphology to analyze complex shapes. This approach aims mainly at the detection of shape bottlenecks which are often of interest in medical imaging because of their anatomical meaning. The detection idea consists in simulating the steady state of an information transmission process between two parts of a complex object in order to highlight bottlenecks as areas of high information flow. This information transmission process is supposed to have a conservative flow which leads to the well-known Dirichlet-Neumann problem. This problem is solved using finite differences, over-relaxation and a raw to fine implementation. The method is applied to the detection of main bottlenecks of brain white matter network, namely corpus callosum, anterior commissure and brain stem.
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The principle of inferring connectivity from local orientation fields can lead to problems as soon as pathways overlap, cross, branch, and have complex geometries.
“Conceptually, the principle of inferring connectivity from local orientation fields can lead to problems as soon as pathways overlap, cross, branch, and have complex geometries7, 35, 36.”
From Tractography-based connectomes are dominated by false-positive connections (2016) · cites this paper as [35]
Regions of white matter bottlenecks have been discussed in the past and highlighted as critical with respect to tractographic findings.
“Regions of white matter bottlenecks have been discussed in the past35 and have been highlighted as critical with respect to tractographic findings36.”
From Tractography-based connectomes are dominated by false-positive connections (2016) · cites this paper as [35]
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Tractography-based connectomes are dominated by false-positive connections
Maier-Hein, K. H., Neher, P., Houde, J.-C., Côté, M.-A., Garyfallidis, E., Zhong, J., Chamberland, M., Yeh, F.-C., Lin, Y.-C., Ji, Q., et al. (2016) · doi:10.1101/084137 · Cited by 1,361 · see citing works
Girard, G., Caminiti, R., Battaglia-Mayer, A., St-Onge, E., Ambrosen, K. S., Eskildsen, S. F., Krug, K., Dyrby, T. B., Descoteaux, M., Thiran, J.-P., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117201 · Cited by 83 · see citing works
- Authors
- Mangin, J.-F., Regis, J., & Frouin, V.
- Affiliations
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
- Venue
- Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis
- Publisher
- IEEE
- Published
- 1996
- Pages
- 319-328
- OpenAlex
- W2071818687
- Cited by
- 27
- References
- 18
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 1 · 2022: 2 · 2020: 2 · 2017: 2 · 2014: 1 · 2013: 1 · 2012: 1
- FWCI
- 0.90
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Image Processing Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Keywords
- conservative flows, Dirichlet-Neumann problem, information flow, shape analysis, medical image analysis, corpus callosum, anterior commissure, brainstem, overrelaxation
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