The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge
-
Published:2021-01
Issue:
Volume:67
Page:101821
-
ISSN:1361-8415
-
Container-title:Medical Image Analysis
-
language:en
-
Short-container-title:Medical Image Analysis
Author:
Heller Nicholas, Isensee Fabian, Maier-Hein Klaus H., Hou Xiaoshuai, Xie Chunmei, Li Fengyi, Nan Yang, Mu Guangrui, Lin Zhiyong, Han Miofei, Yao Guang, Gao YaozongORCID, Zhang Yao, Wang Yixin, Hou Feng, Yang Jiawei, Xiong Guangwei, Tian Jiang, Zhong Cheng, Ma JunORCID, Rickman Jack, Dean Joshua, Stai Bethany, Tejpaul ReshaORCID, Oestreich Makinna, Blake Paul, Kaluzniak Heather, Raza ShaneabbasORCID, Rosenberg JoelORCID, Moore Keenan, Walczak EdwardORCID, Rengel Zachary, Edgerton Zach, Vasdev Ranveer, Peterson MatthewORCID, McSweeney Sean, Peterson SarahORCID, Kalapara Arveen, Sathianathen Niranjan, Papanikolopoulos Nikolaos, Weight ChristopherORCID
Funder
National Cancer Institute
Subject
Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology
Reference69 articles.
1. Deep learning of representations for unsupervised and transfer learning;Bengio,2012 2. Automatic renal nephrometry scoring using machine learning;Blake;European Urology Supplements,2019 3. Nipy/nibabel: 2.3. 0;Brett;June,2018
Cited by
211 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|