Simon Fraser University

U-Net: Convolutional Networks for Biomedical Image Segmentation

In this paper, the authors proposed a fully convolutional neural network architecture for biomedical image segmentation which overcame the limitations of the contemporary algorithms. Unlike other ...
Simon Fraser University

V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

This paper proposes an end-to-end trained fully convolutional neural network model to process 3D image volumes. Unlike previous works that processed the input volumes slice-wise or patch-wise, the ...
EurekAlert!

Advanced U-net segmentation model using residual grouped convolution and attention mechanism for brain tumor MRI image segmentation

Through a comprehensive evaluation of model complexity and number of parameters, it was determined that the overall performance of the proposed model is the best when eight group convolutions are used ...