Abstract
The volume of white matter in brain MR image is important for medical diagnosis, therefore, it is critical to obtain an accurate segmentation of the white matter. We compare quantitatively the up-to-date versions of three software packages: SPM, FSL, and FreeSurfer, for brain MR image segmentation, and then select the package that performs the best for white matter segmentation. Dice index (DSC), Hausdorff distance (HD), and modified Hausdorff distance (MHD) are chosen as the metrics for comparison. A new computational method is also proposed to calculate HD and MHD efficiently.
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Li, X., Martinez, J. (2020). Quantitative Comparison of White Matter Segmentation for Brain MR Images. In: Arai, K., Kapoor, S. (eds) Advances in Computer Vision. CVC 2019. Advances in Intelligent Systems and Computing, vol 943. Springer, Cham. https://doi.org/10.1007/978-3-030-17795-9_46
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DOI: https://doi.org/10.1007/978-3-030-17795-9_46
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