Automatic 3D liver location and segmentation via convolutional neural network and graph cut 肝脏分割

Purpose Segmentation of the liver from abdominal computed tomography (CT) images is an essential step in some computer-assisted clinical interventions, such as surgery planning for living donor liver transplant, radiotherapy and volume measurement. In this work, we develop a deep learning algorithm with graph cut refinement to automatically segment the liver in CT scans. Methods The proposed method consists of two main steps:(i) simultaneously liver detection and probabilistic segmentation using 3D convolutional neural network; (ii) accuracy refinement of the initial segmentation with graph cut and the previously learned probability map.
Results The proposed approach was validated on forty CT volumes ta