2016
Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation
NeurIPS 2016poster
Segmentation of 3D images is a fundamental problem in biomedical image analysis. Deep learning (DL) approaches have achieved the state-of-the-art segmentation performance. To exploit the 3D contexts using neural networks, known DL segmentation methods, including 3D convolution, 2D convolution on the…