Segmentation of Brain Tumor from MR Images using the Hybrid Architecture: “BConvLSTMSegX-Net”
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Abstract
In medical image segmentation, deep learning-based network methods perform well, during the
last few years, most of them are using U-Net, X-Net and SegNet. In this paper, we propose
hybrid BConvLSTMSegX-Net with the concatenation of SegNet and X-Net. Instead of simply
adding skip connections in SegX-Net, we take full advantage of BConvLSTM and also batch
normalization is used to accelerate the network. Experimentation is carried out and the results are
obtained for segmentation of brain tumor obtained Accuracy:0.98, Specificity:0.96,
Precision:1.00 & F1- Score:0.95.
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