Department of Radiology, Graduate School of Medicine Osaka University, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan;
Children's National Medical Center, 111 Michigan Ave., N.W Washington, D.C 20010, USA;
Graduate School of Information Science and Engineering, Ritsumeikan University,1-1-1, Nojihigashi, Kusatsu, Shiga, Japan;
Department of Radiology, Graduate School of Medicine Osaka University, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan;
National Institutes of Health, Clinical Center, Radiology and Imaging Sciences, 10 Center Drive Bethesda, MD 20892, USA;
Graduate School of Information Science and Engineering, Ritsumeikan University,1-1-1, Nojihigashi, Kusatsu, Shiga, Japan;
Department of Radiology, Graduate School of Medicine Osaka University, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan;
Department of Radiology, Graduate School of Medicine Osaka University, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan;
statistical shape prediction; statistical shape model; probabilistic atlas;
机译:使用条件形状定位和无监督先验先验从CT图像进行腹部多器官分割
机译:基于3D贴片的深卷积神经网络的腹部多器官自动分割
机译:具有轻松条件分层统计形状模型的多器官分割
机译:基于3D腹部CT图像空间划分的概率图集的多器官分割
机译:通过递增级联学习和基于回归的可变形模型对CT盆腔器官进行精确分割。
机译:使用条件形状定位和无监督先验先验从CT图像进行腹部多器官分割
机译:使用分层加权对象特定地图集的多器官腹部CT分割