ArticleComputational and mathematical methods in medicine2018
Automatic Extraction of the Centerline of Corpus Callosum from Segmented Mid-Sagittal MR Images.
Article in Computational and mathematical methods in medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Automatic, Age Consistent Reconstruction of the Corpus Callosum Guided by Coherency From In Utero Diffusion-Weighted MRI.IEEE transactions on medical imaging · 2020Article
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4 authors.
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Abstract
The centerline, as a simple and compact representation of object shape, has been used to analyze variations of the human callosal shape. However, automatic extraction of the callosal centerline remains a sophisticated problem. In this paper, we propose a method of automatic extraction of the callosal centerline from segmented mid-sagittal magnetic resonance (MR) images. A model-based point matching method is introduced to localize the anterior and posterior endpoints of the centerline. The model of the endpoint is constructed with a statistical descriptor of the shape context. Active contour modeling is adopted to drive the curve with the fixed endpoints to approximate the centerline using the gradient of the distance map of the segmented corpus callosum. Experiments with 80 segmented mid-sagittal MR images were performed. The proposed method is compared with a skeletonization method and an interactive method in terms of recovery error and reproducibility. Results indicate that the proposed method outperforms skeletonization and is comparable with and sometimes better than the interactive method.
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