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Proceedings ArticleDOI

Corpus callosum parcellation methods: a quantitative comparative study

TLDR
This work presents a quantitative analysis of different state of art CC parcellation methods aiming to compare their results on a common dataset and shows a significant difference among the same CC parcels, but using different CC par cellation methods, and its impact on the diffusion properties.
Abstract
Corpus Callosum (CC) is the largest white matter structure and it plays a crucial role in clinical and research studies due to its shape and volume correlation to subject’s characteristics and neurodegenerative diseases. CC segmentation and parcellation are an important step for any MRI-based clinical and research study. There is only a few automatic CC parcellation methods proposed in the literature and, since it is not trivial to build a ground truth, most methods are validated qualitatively. We present a quantitative analysis of different state of art CC parcellation methods aiming to compare their results on a common dataset. Our findings show a significant difference among the same CC parcels, but using different CC parcellation methods, and its impact on the diffusion properties.

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Citations
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Proceedings ArticleDOI

Comparative Study of Deep Learning Models for Segmentation of Corpus Callosum

TL;DR: A comparative study of three deep learning models such as CE- net, UNet++ & MultiResUNet for the segmentation of Corpus Callosum in the Brain MRI images using the dataset acquired from open source ABIDE platform finds CE-Net gave the best dice similarity coefficient score, among all the three Deep Learning models.
References
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Journal ArticleDOI

Toward a quantitative assessment of diffusion anisotropy

TL;DR: New indices calculated from the entire diffusion tensor are rotationally invariant (RI) and show that anisotropy is highly variable in different white matter regions depending on the degree of coherence of fiber tract directions.
Journal ArticleDOI

Hand and sex differences in the isthmus and genu of the human corpus callosum. A postmortem morphological study

TL;DR: The midsagittal area of the corpus callosum was measured in its entirety and in seven subdivisions in a sample of 50 brains consecutively obtained from autopsies of individuals who had neuropsychological testing before death.
Journal ArticleDOI

Topography of the human corpus callosum revisited--comprehensive fiber tractography using diffusion tensor magnetic resonance imaging.

TL;DR: DTI-based fiber tractography of healthy human subjects suggests a modification of the widely accepted Witelson scheme and a new classification of vertical CC partitions.
Journal ArticleDOI

Diffusion tensor imaging of the corpus callosum in Autism

TL;DR: The results suggest that the microstructure of the corpus callosum is affected in autism, which may be related to nonverbal cognitive performance.
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