Deep CNN for Brain Tumor Classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software
Link
http://link.springer.com/content/pdf/10.1007/s11063-020-10398-2.pdf
Reference72 articles.
1. Razzak MI, Imran M, Xu G (2018) Efficient brain tumor segmentation with multiscale two-pathway-group conventional neural networks. IEEE J Biomed Health Inform 23(5):1911–1919
2. Siegel RL, Miller KD (2017) Jemal ACancer statistics, 2017. CA Cancer J Clin 67(1):7–30
3. Zhang Y, Li A, Peng C, Wang M (2016) Improve glioblastoma multiforme prognosis prediction by using feature selection and multiple kernel learning. IEEE/ACM Trans Comput Biol Bioinform 13(5):825–835
4. Yang Y, Yan LF, Zhang X, Han Y, Nan HY, Hu YC, Ge XW (2018) Glioma grading on conventional MR images: a deep learning study with transfer learning. Front Neurosci 12:804
5. Talo M, Baloglu UB, Yıldırım Ö, Acharya UR (2019) Application of deep transfer learning for automated brain abnormality classification using MR images. Cogn Syst Res 54:176–188
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