MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge

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

IEEE Transactions on Medical Imaging（2021）

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摘要

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...

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关键词

Annotations,Image segmentation,Tumors,Computer architecture,Training,Task analysis,Semantics

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