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.
Mariana Pereira, Giovana Cover , Simone Appenzeller, and Leticia Rittner, "Corpus callosum parcellation methods: a quantitative comparative study," Proc. SPIE 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1057817 (Presented at SPIE Medical Imaging: February 13, 2018; Published: 12 March 2018); https://doi.org/10.1117/12.2296617.
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