Presentation + Paper
12 March 2018 Automatic callosal fiber convergence plane computation through DTI-based divergence map
Author Affiliations +
Abstract
The Corpus Callosum (CC) is the largest white matter structure in the brain and subject of many relevant studies. In order to properly analyze this structure in 2D studies, the midsagittal plane (MSP) determination of the CC is required. Usually, this computation is done on structural MR images and transformed to diffusion space when necessary. Furthermore, most existing methods take into account the whole brain structure instead of only the object of study. Differently, our work proposes a plane computation based on the structure of interest, directly on Diffusion Tensor Images (DTI), through the DTI-based divergence map.1 Since our plane is computed in the diffusion domain, the method explores the high organization of the fibers in the CC to establish a reference system that can be used to perform 2D CC studies, while most existing MSP computation algorithms are based on structural characteristics of the brain, such as shape symmetry and inter-hemispheric fissure location. Experiments showed that the proposed method is reliable regarding repeatability and parameters choices. Results also indicate that the callosal fiber convergence plane (CFCP) found by our method is similar to MSP in most subjects. Nevertheless, when the CC is not well aligned with the brain intercommissural fissure, CFCP and MSP presented significant differences.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gustavo R. Pinheiro, Giovana S. Cover, Mariana P. Bento, and Leticia Rittner "Automatic callosal fiber convergence plane computation through DTI-based divergence map", Proc. SPIE 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1057815 (12 March 2018); https://doi.org/10.1117/12.2293381
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Diffusion tensor imaging

Brain

Diffusion

Magnetic resonance imaging

Structured optical fibers

Brain mapping

Data conversion

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