Deep Learning Systems for Automated Segmentation of Brain Tissues and Tumors in MRIs
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-62554-2_1
Reference29 articles.
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2. Ghosh, P., Mali, K., Das, S.K.: Chaotic firefly algorithm-based fuzzy C-means algorithm for segmentation of brain tissues in magnetic resonance images. J. Vis. Commun. Image Represent. 54, 63–79 (2018)
3. Namburu, A., Samayamantula, S.K., Edara, S.R.: Generalised rough intuitionistic fuzzy c-means for magnetic resonance brain image segmentation. IET Image Proc. 11(9), 777–785 (2017)
4. Singh, C., Bala, A.: A DCT-based local and non-local fuzzy C-means algorithm for segmentation of brain magnetic resonance images. Appl. Soft Comput. 68, 447–457 (2018)
5. Narayanan, A., Rajasekaran, M.P., Zhang, Y., Govindaraj, V., Thiyagarajan, A.: Multi-channeled MR brain image segmentation: a novel double optimization approach combined with clustering technique for tumor identification and tissue segmentation. Biocybern. Biomed. Eng. 39(2), 350–381 (2019)
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