Locally-Constrained Region-Based Methods for DW-MRI Segmentation
Abstract
In this paper, we describe a method for segmenting fiber bundles from diffusion-weighted magnetic resonance images using a locally-constrained region based approach. From a pre-computed optimal path, the algorithm propagates outward capturing only those voxels which are locally connected to the fiber bundle. Rather than attempting to find large numbers of open curves or single fibers, which individually have questionable meaning, this method segments the full fiber bundle region. The strengths of this approach include its ease-of-use, computational speed, and applicability to a wide range of fiber bundles. In this work, we show results for segmenting the cingulum bundle. Finally, we explain how this approach and extensions thereto overcome a major problem that typical region-based flows experience when attempting to segment neural fiber bundles.
Cite
Text
Melonakos et al. "Locally-Constrained Region-Based Methods for DW-MRI Segmentation." IEEE/CVF International Conference on Computer Vision, 2007. doi:10.1109/ICCV.2007.4409167Markdown
[Melonakos et al. "Locally-Constrained Region-Based Methods for DW-MRI Segmentation." IEEE/CVF International Conference on Computer Vision, 2007.](https://mlanthology.org/iccv/2007/melonakos2007iccv-locally/) doi:10.1109/ICCV.2007.4409167BibTeX
@inproceedings{melonakos2007iccv-locally,
title = {{Locally-Constrained Region-Based Methods for DW-MRI Segmentation}},
author = {Melonakos, John and Niethammer, Marc and Mohan, Vandana and Kubicki, Marek and Miller, James V. and Tannenbaum, Allen R.},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {2007},
pages = {1-8},
doi = {10.1109/ICCV.2007.4409167},
url = {https://mlanthology.org/iccv/2007/melonakos2007iccv-locally/}
}