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 authors propose to use volumetric convolutions. Moreover, a new objective function formulated using the Dice coefficient is proposed to be optimized, and the authors demonstrate the fast and superior performance of the algorithm on the segmentation of prostate MRI volumes. ...