arXiv 2303.062742023-03-14cs.CVcs.LG

CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

University of Warwick（华威大学）；Histofy Ltd（Histofy有限公司）；EPFL（洛桑联邦理工学院）；The University of Hong Kong（香港大学）；Tencent AI Lab（腾讯AI实验室）；Sichuan University（四川大学）；Tsinghua University（清华大学）；Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association（亥姆霍兹协会马克斯·德尔布吕克分子医学中心）；Humboldt University of Berlin（柏林洪堡大学）；Charité University Medicine（柏林夏里特医学院）；University of Bern（伯尔尼大学）；University of Cambridge（剑桥大学）；Chinese University of Hong Kong（香港中文大学）；Arontier Co. Ltd（Arontier有限公司）；Mohamed Bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；CNRS（法国国家科学研究中心）；IFCE（法国马与骑术研究所）；INRAE（法国国家农业、食品与环境研究院）；Université de Tours（图尔大学）；Institut de Génétique et de Biologie Moléculaire et Cellulaire（分子与细胞遗传学与生物学研究所）；Centre National de la Recherche Scientifique（法国国家科学研究中心）；Institut National de la Santé et de la Recherche Médicale（法国国家健康与医学研究院）；Université de Strasbourg（斯特拉斯堡大学）；Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院）；South China University of Technology（华南理工大学）；University Hospitals Coventry and Warwickshire NHS Trust（考文垂与沃里克郡大学医院NHS信托）

Simon Graham, Quoc Dang Vu, Mostafa Jahanifar, Martin Weigert, Uwe Schmidt, Wenhua Zhang, Jun Zhang, Sen Yang, Jinxi Xiang, Xiyue Wang, Josef Lorenz Rumberger, … 展开作者

Simon Graham, Quoc Dang Vu, Mostafa Jahanifar, Martin Weigert, Uwe Schmidt, Wenhua Zhang, Jun Zhang, Sen Yang, Jinxi Xiang, Xiyue Wang, Josef Lorenz Rumberger, Elias Baumann, Peter Hirsch, Lihao Liu, Chenyang Hong, Angelica I. Aviles-Rivero, Ayushi Jain, Heeyoung Ahn, Yiyu Hong, Hussam Azzuni, Min Xu, Mohammad Yaqub, Marie-Claire Blache, Benoît Piégu, Bertrand Vernay, Tim Scherr, Moritz Böhland, Katharina Löffler, Jiachen Li, Weiqin Ying, Chixin Wang, Dagmar Kainmueller, Carola-Bibiane Schönlieb, Shuolin Liu, Dhairya Talsania, Yughender Meda, Prakash Mishra, Muhammad Ridzuan, Oliver Neumann, Marcel P. Schilling, Markus Reischl, Ralf Mikut, Banban Huang, Hsiang-Chin Chien, Ching-Ping Wang, Chia-Yen Lee, Hong-Kun Lin, Zaiyi Liu, Xipeng Pan, Chu Han, Jijun Cheng, Muhammad Dawood, Srijay Deshpande, Raja Muhammad Saad Bashir, Adam Shephard, Pedro Costa, João D. Nunes, Aurélio Campilho, Jaime S. Cardoso, Hrishikesh P S, Densen Puthussery, Devika R G, Jiji C, Ye Zhang, Zijie Fang, Zhifan Lin, Yongbing Zhang, Chunhui Lin, Liukun Zhang, Lijian Mao, Min Wu, Vi Thi-Tuong Vo, Soo-Hyung Kim, Taebum Lee, Satoshi Kondo, Satoshi Kasai, Pranay Dumbhare, Vedant Phuse, Yash Dubey, Ankush Jamthikar, Trinh Thi Le Vuong, Jin Tae Kwak, Dorsa Ziaei, Hyun Jung, Tianyi Miao, David Snead, Shan E Ahmed Raza, Fayyaz Minhas, Nasir M. Rajpoot

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英文摘要：

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest available dataset of its kind to assess nuclear segmentation and cellular composition. Our challenge, named CoNIC, stimulated the development of reproducible algorithms for cellular recognition with real-time result inspection on public leaderboards. We conducted an extensive post-challenge analysis based on the top-performing models using 1,658 whole-slide images of colon tissue. With around 700 million detected nuclei per model, associated features were used for dysplasia grading and survival analysis, where we demonstrated that the challenge's improvement over the previous state-of-the-art led to significant boosts in downstream performance. Our findings also suggest that eosinophils and neutrophils play an important role in the tumour microevironment. We release challenge models and WSI-level results to foster the development of further methods for biomarker discovery.

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