PMID- 36179380
OWN - NLM
STAT- MEDLINE
DCOM- 20221024
LR  - 20221122
IS  - 1361-8423 (Electronic)
IS  - 1361-8415 (Linking)
VI  - 82
DP  - 2022 Nov
TI  - Fast and Low-GPU-memory abdomen CT organ segmentation: The FLARE challenge.
PG  - 102616
LID - S1361-8415(22)00244-4 [pii]
LID - 10.1016/j.media.2022.102616 [doi]
AB  - Automatic segmentation of abdominal organs in CT scans plays an important role in 
      clinical practice. However, most existing benchmarks and datasets only focus on 
      segmentation accuracy, while the model efficiency and its accuracy on the testing 
      cases from different medical centers have not been evaluated. To comprehensively 
      benchmark abdominal organ segmentation methods, we organized the first Fast and 
      Low GPU memory Abdominal oRgan sEgmentation (FLARE) challenge, where the 
      segmentation methods were encouraged to achieve high accuracy on the testing 
      cases from different medical centers, fast inference speed, and low GPU memory 
      consumption, simultaneously. The winning method surpassed the existing 
      state-of-the-art method, achieving a 19x faster inference speed and reducing the 
      GPU memory consumption by 60% with comparable accuracy. We provide a summary of 
      the top methods, make their code and Docker containers publicly available, and 
      give practical suggestions on building accurate and efficient abdominal organ 
      segmentation models. The FLARE challenge remains open for future submissions 
      through a live platform for benchmarking further methodology developments at 
      https://flare.grand-challenge.org/.
CI  - Copyright (c) 2022 Elsevier B.V. All rights reserved.
FAU - Ma, Jun
AU  - Ma J
AD  - Department of Mathematics, Nanjing University of Science and Technology, 210094, 
      Nanjing, China.
FAU - Zhang, Yao
AU  - Zhang Y
AD  - Institute of Computing Technology, Chinese Academy of Sciences and the University 
      of Chinese Academy of Sciences, 100019, Beijing, China.
FAU - Gu, Song
AU  - Gu S
AD  - Department of Image Reconstruction, Nanjing Anke Medical Technology Co., Ltd., 
      211113, Nanjing, China.
FAU - An, Xingle
AU  - An X
AD  - Infervision Technology Co. Ltd., 100020, Beijing, China.
FAU - Wang, Zhihe
AU  - Wang Z
AD  - Shenzhen Haichuang Medical Co., Ltd., 518049, Shenzhen, China.
FAU - Ge, Cheng
AU  - Ge C
AD  - Institute of Bioinformatics and Medical Engineering, Jiangsu University of 
      Technology, 213001, Changzhou, China.
FAU - Wang, Congcong
AU  - Wang C
AD  - School of Computer Science and Engineering, Tianjin University of Technology, 
      300384, Tianjin, China; Engineering Research Center of Learning-Based Intelligent 
      System, Ministry of Education, 300384, Tianjin, China.
FAU - Zhang, Fan
AU  - Zhang F
AD  - Radiological Algorithm, Fosun Aitrox Information Technology Co., Ltd., 200033, 
      Shanghai, China.
FAU - Wang, Yu
AU  - Wang Y
AD  - Radiological Algorithm, Fosun Aitrox Information Technology Co., Ltd., 200033, 
      Shanghai, China.
FAU - Xu, Yinan
AU  - Xu Y
AD  - Key Lab of Intelligent Perception and Image Understanding of Ministry of 
      Education, Xidian University, 710071, Shaanxi, China.
FAU - Gou, Shuiping
AU  - Gou S
AD  - Key Lab of Intelligent Perception and Image Understanding of Ministry of 
      Education, Xidian University, 710071, Shaanxi, China.
FAU - Thaler, Franz
AU  - Thaler F
AD  - Gottfried Schatz Research Center: Biophysics, Medical University of Graz, 8010, 
      Graz, Austria; Institute of Computer Graphics and Vision, Graz University of 
      Technology, 8010, Graz, Austria.
FAU - Payer, Christian
AU  - Payer C
AD  - Institute of Computer Graphics and Vision, Graz University of Technology, 8010, 
      Graz, Austria.
FAU - Stern, Darko
AU  - Stern D
AD  - Gottfried Schatz Research Center: Biophysics, Medical University of Graz, 8010, 
      Graz, Austria.
FAU - Henderson, Edward G A
AU  - Henderson EGA
AD  - Division of Cancer Sciences, The University of Manchester, M139PL, Manchester, 
      UK; Radiotherapy Related Research, The Christie NHS Foundation Trust, M139PL, 
      Manchester, UK.
FAU - McSweeney, Donal M
AU  - McSweeney DM
AD  - Division of Cancer Sciences, The University of Manchester, M139PL, Manchester, 
      UK; Radiotherapy Related Research, The Christie NHS Foundation Trust, M139PL, 
      Manchester, UK.
FAU - Green, Andrew
AU  - Green A
AD  - Division of Cancer Sciences, The University of Manchester, M139PL, Manchester, 
      UK; Radiotherapy Related Research, The Christie NHS Foundation Trust, M139PL, 
      Manchester, UK.
FAU - Jackson, Price
AU  - Jackson P
AD  - Peter MacCallum Cancer Centre, 3000, Melbourne, Australia.
FAU - McIntosh, Lachlan
AU  - McIntosh L
AD  - Peter MacCallum Cancer Centre, 3000, Melbourne, Australia.
FAU - Nguyen, Quoc-Cuong
AU  - Nguyen QC
AD  - University of Information Technology, VNU-HCM, 700000, Ho Chi Minh City, Viet 
      Nam.
FAU - Qayyum, Abdul
AU  - Qayyum A
AD  - Brest National School of Engineering, UMR CNRS 6285 LabSTICC, 29280, Brest, 
      France.
FAU - Conze, Pierre-Henri
AU  - Conze PH
AD  - IMT Atlantique, LaTIM UMR 1101, Inserm, 29238, Brest, France.
FAU - Huang, Ziyan
AU  - Huang Z
AD  - Institute of Medical Robotics, Shanghai Jiao Tong University, 200240, Shanghai, 
      China.
FAU - Zhou, Ziqi
AU  - Zhou Z
AD  - Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen 
      University, 518000, Shenzhen, China.
FAU - Fan, Deng-Ping
AU  - Fan DP
AD  - College of Computer Science, Nankai University, 300071, Tianjin, China; Inception 
      Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates.
FAU - Xiong, Huan
AU  - Xiong H
AD  - Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab 
      Emirates; Harbin Institute of Technology, 150001, Harbin, China.
FAU - Dong, Guoqiang
AU  - Dong G
AD  - Department of Nuclear Medicine, Nanjing Drum Tower Hospital, the Affiliated 
      Hospital of Nanjing University Medical School, 210008, Nanjing, China; Department 
      of Interventional Radiology, The Second Affiliated Hospital of Bengbu Medical 
      College, 233017, Bengbu, China.
FAU - Zhu, Qiongjie
AU  - Zhu Q
AD  - Department of Nuclear Medicine, Nanjing Drum Tower Hospital, the Affiliated 
      Hospital of Nanjing University Medical School, 210008, Nanjing, China; Department 
      of Radiology, Shidong Hospital, 200438, Shanghai, China.
FAU - He, Jian
AU  - He J
AD  - Department of Nuclear Medicine, Nanjing Drum Tower Hospital, the Affiliated 
      Hospital of Nanjing University Medical School, 210008, Nanjing, China.
FAU - Yang, Xiaoping
AU  - Yang X
AD  - Department of Mathematics, Nanjing University, 210093, Nanjing, China. Electronic 
      address: xpyang@nju.edu.cn.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20220913
PL  - Netherlands
TA  - Med Image Anal
JT  - Medical image analysis
JID - 9713490
SB  - IM
MH  - Humans
MH  - *Algorithms
MH  - *Tomography, X-Ray Computed/methods
MH  - Abdomen/diagnostic imaging
MH  - Benchmarking
MH  - Image Processing, Computer-Assisted/methods
OTO - NOTNLM
OT  - Abdominal organ
OT  - Efficiency
OT  - Multi-center
OT  - Segmentation
COIS- Declaration of Competing Interest The authors declare that they have no known 
      competing financial interests or personal relationships that could have appeared 
      to influence the work reported in this paper.
EDAT- 2022/10/01 06:00
MHDA- 2022/10/25 06:00
CRDT- 2022/09/30 18:13
PHST- 2022/01/13 00:00 [received]
PHST- 2022/06/26 00:00 [revised]
PHST- 2022/09/02 00:00 [accepted]
PHST- 2022/10/01 06:00 [pubmed]
PHST- 2022/10/25 06:00 [medline]
PHST- 2022/09/30 18:13 [entrez]
AID - S1361-8415(22)00244-4 [pii]
AID - 10.1016/j.media.2022.102616 [doi]
PST - ppublish
SO  - Med Image Anal. 2022 Nov;82:102616. doi: 10.1016/j.media.2022.102616. Epub 2022 
      Sep 13.