Skip NavigationSkip to Content
Return Return to Search Results

MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge

  1. Author:
    Verma, Ruchika
    Kumar, Neeraj
    Patil, Abhijeet
    Kurian, Nikhil Cherian
    Rane, Swapnil
    Graham, Simon
    Zwager, Mieke
    Raza, Shan E. Ahmed
    Rajpoot, Nasir
    Wu, Xiyi
    Chen, Huai
    Huang, Yijie
    Wang, Lisheng
    Jung,Hyun
    Brown, G. Thomas
    Liu,Yanling
    Liu, Shuolin
    Jahromi, Seyed Alireza Fatemi
    Khani, Ali Asghar
    Montahaei, Ehsan
    Baghshah, Mahdieh Soleymani
    Behroozi, Hamid
    Semkin, Pavel
    Rassadin, Alexandr
    Dutande, Prasad
    Lodaya, Romil
    Baid, Ujjwal
    Baheti, Bhakti
    Talbar, Sanjay
    Mahbod, Amirreza
    Ecker, Rupert
    Ellinger, Isabella
    Luo, Zhipeng
    Dong, Bin
    Xu, Zhengyu
    Yao, Yuehan
    Lv, Shuai
    Feng, Ming
    Xu, Kele
    Zunair, Hasib
    Ben Hamza, Abdessamad
    Smiley, Steven
    Yin, Tang-Kai
    Fang, Qi-Rui
    Srivastava, Shikhar
    Mahapatra, Dwarikanath
    Trnavska, Lubomira
    Zhang, Hanyun
    Narayanan, Priya Lakshmi
    Law, Justin
    Yuan, Yinyin
    Tejomay, Abhiroop
    Mitkari, Aditya
    Koka, Dinesh
    Ramachandra, Vikas
    Kini, Lata
    Sethi, Amit

  2. Author Address

    Case Western Reserve Univ, Dept Biomed Engn, Cleveland, OH 44106 USA.Univ Alberta, Dept Comp Sci, Edmonton, AB T6G 2R3, Canada.Alberta Machine Intelligence Inst, Edmonton, AB T5J 3B1, Canada.Indian Inst Technol, Dept Elect Engn, Mumbai 400076, Maharashtra, India.HBNI, Tata Mem Ctr ACTREC, Dept Pathol, Mumbai 400012, Maharashtra, India.Univ Warwick, Dept Comp Sci, Coventry CV4 7AL, W Midlands, England.Univ Groningen, Dept Pathol, NL-9712 Groningen, Netherlands.Shanghai Jiao Tong Univ, Inst Image Proc & Pattern Recognit, Dept Automat, Shanghai 200240, Peoples R China.NCI, Adv Biomed Comp Sci, Frederick Natl Lab Canc Res, Frederick, MD 21702 USA.Anhui Univ, Dept Elect Engn & Automat, Hefei 230039, Peoples R China.Sharif Univ Technol, Dept Comp Engn, Tehran 113658639, Iran.Sharif Univ Technol, Dept Elect Engn, Tehran 113658639, Iran.Xperience AI, Nizhnii Novgorod 603155, Russia.SGGS Inst Engn & Technol, Ctr Excellence Signal & Image Proc, Nanded 431606, India.Med Univ Vienna, Inst Pathophysiol & Allergy Res, A-1090 Vienna, Austria.TissueGnostics GmbH, Dept Res & Dev, Vienna, Austria.DeepBlue Technol Shanghai Co Ltd, Shanghai 200336, Peoples R China.Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Peoples R China.Tongji Univ, Sch Elect & Informat Engn, Shanghai 200092, Peoples R China.Natl Univ Def Technol, Natl Key Lab Parallel & Distributed Proc, Changsha 410073, Peoples R China.Concordia Univ, Concordia Inst Informat Syst Engn, Montreal, PQ H4B 1R6, Canada.Jensen Hughes, Site Risk Management Engineer, Liverpool, NY 13212 USA.Natl Univ Kaohsiung, Dept Comp Sci & Informat Engn, Kaohsiung 811, Taiwan.Incept Inst Artificial Intelligence, Abu Dhabi, U Arab Emirates.Slovak Univ Technol Bratislava, Fac Informat & Informat Technol, Bratislava 81107, Slovakia.Inst Canc Res, Ctr Evolut & Canc, London SW7 3RP, England.Inst Canc Res, Div Mol Pathol, London SW7 3RP, England.Onward Hlth, Hyderabad 500032, India.
    1. Year: 2021
    2. Date: June 4
  2. Journal: IEEE Transactions on Medical Imaging
  3. IEEE-Inst Electrical Electronics Engineers Inc.
    1. 40
    2. 12
    3. Pages: 3413-3423
  5. Type of Article: Article
  6. ISSN: 0278-0062
  1. Abstract:

    Detecting various types of cells in and around the tumor matrix holds a special significance in characterizing the tumor micro-environment for cancer prognostication and research. Automating the tasks of detecting, segmenting, and classifying nuclei can free up the pathologists' time for higher value tasks and reduce errors due to fatigue and subjectivity. To encourage the computer vision research community to develop and test algorithms for these tasks, we prepared a large and diverse dataset of nucleus boundary annotations and class labels. The dataset has over 46,000 nuclei from 37 hospitals, 71 patients, four organs, and four nucleus types. We also organized a challenge around this dataset as a satellite event at the International Symposium on Biomedical Imaging (ISBI) in April 2020. The challenge saw a wide participation from across the world, and the top methods were able to match inter-human concordance for the challenge metric. In this paper, we summarize the dataset and the key findings of the challenge, including the commonalities and differences between the methods developed by various participants. We have released the MoNuSAC2020 dataset to the public.

    See More

  1. Keywords:

External Sources

  1. View Full Text
  2. DOI: 10.1109/TMI.2021.3085712
  3. View record in Web of Science®
  4. WOS: 000724511900015

Library Notes

  1. Fiscal Year: FY2021-2022
NCI at Frederick

You are leaving a government website.

This external link provides additional information that is consistent with the intended purpose of this site. The government cannot attest to the accuracy of a non-federal site.

Linking to a non-federal site does not constitute an endorsement by this institution or any of its employees of the sponsors or the information and products presented on the site. You will be subject to the destination site's privacy policy when you follow the link.

ContinueCancel