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Brain MRI Tumor Segmentation with Adversarial Networks
[article]
2020
arXiv
pre-print
Deep Learning is a promising approach to either automate or simplify several tasks in the healthcare domain. In this work, we introduce SegAN-CAT, an approach to brain tumor segmentation in Magnetic Resonance Images (MRI), based on Adversarial Networks. In particular, we extend SegAN, successfully applied to the same task in a previous work, in two respects: (i) we used a different model input and (ii) we employed a modified loss function to train the model. We tested our approach on two large
arXiv:1910.02717v2
fatcat:bf4zwamknbeijgp56rr6f4fj5e