An Improved Full Convolutional Network Combined with Conditional Random Fields for Brain MR Image Segmentation Algorithm and its 3D Visualization Analysis
Author:
Publisher
Springer Science and Business Media LLC
Subject
Health Information Management,Health Informatics,Information Systems,Medicine (miscellaneous)
Link
http://link.springer.com/content/pdf/10.1007/s10916-019-1424-0.pdf
Reference34 articles.
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3. Sauwen, N., Acou, M., Sima, D. M. et al., Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization[J]. BMC Medical Imaging 17(1):11–19, 2017.
4. Gholipour, A., Rollins, C. K., Velasco-Annis, C. et al., A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth[J]. Scientific Reports 7(1):476–488, 2017.
5. Heudorfer, L., and Stammberger, T., Optimization and validation of a rapid high-resolution T1-w 3D FLASH water excitation MRI sequence for the quantitative assessment of articular cartilage volume and thickness - magnetic resonance imaging[J]. Magnetic Resonance Imaging 19(2):177–185, 2001.
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