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Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge.
Veta, Mitko; Heng, Yujing J; Stathonikos, Nikolas; Bejnordi, Babak Ehteshami; Beca, Francisco; Wollmann, Thomas; Rohr, Karl; Shah, Manan A; Wang, Dayong; Rousson, Mikael; Hedlund, Martin; Tellez, David; Ciompi, Francesco; Zerhouni, Erwan; Lanyi, David; Viana, Matheus; Kovalev, Vassili; Liauchuk, Vitali; Phoulady, Hady Ahmady; Qaiser, Talha; Graham, Simon; Rajpoot, Nasir; Sjöblom, Erik; Molin, Jesper; Paeng, Kyunghyun; Hwang, Sangheum; Park, Sunggyun; Jia, Zhipeng; Chang, Eric I-Chao; Xu, Yan; Beck, Andrew H; van Diest, Paul J; Pluim, Josien P W.
Affiliation
  • Veta M; Medical Image Analysis Group, Eindhoven University of Technology, Eindhoven, the Netherlands. Electronic address: m.veta@tue.nl.
  • Heng YJ; Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
  • Stathonikos N; Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands.
  • Bejnordi BE; Diagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, the Netherlands.
  • Beca F; Department of Pathology, Stanford University School of Medicine, USA.
  • Wollmann T; Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB and DKFZ, Heidelberg, Germany.
  • Rohr K; Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB and DKFZ, Heidelberg, Germany.
  • Shah MA; The Harker School, San Jose, USA.
  • Wang D; Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
  • Rousson M; ContextVision AB, Linköping, Sweden.
  • Hedlund M; ContextVision AB, Linköping, Sweden.
  • Tellez D; Department of Pathology, Stanford University School of Medicine, USA.
  • Ciompi F; Department of Pathology, Stanford University School of Medicine, USA.
  • Zerhouni E; Foundations of Cognitive Computing, IBM Research Zürich, Rüschlikon, Switzerland.
  • Lanyi D; Foundations of Cognitive Computing, IBM Research Zürich, Rüschlikon, Switzerland.
  • Viana M; Visual Analytics and Insights, IBM Research Brazil, São Paulo, Brazil.
  • Kovalev V; Biomedical Image Analysis Department, United Institute of Informatics, Minsk, Belarus.
  • Liauchuk V; Biomedical Image Analysis Department, United Institute of Informatics, Minsk, Belarus.
  • Phoulady HA; Department of Computer Science and Engineering, University of South Florida, Tampa, FL, USA.
  • Qaiser T; Department of Computer Science, University of Warwick, Warwick, UK.
  • Graham S; Department of Computer Science, University of Warwick, Warwick, UK.
  • Rajpoot N; Department of Computer Science, University of Warwick, Warwick, UK.
  • Sjöblom E; Research, Sectra, Linköping, Sweden.
  • Molin J; Research, Sectra, Linköping, Sweden.
  • Paeng K; Lunit Inc., Seoul, South Korea.
  • Hwang S; Lunit Inc., Seoul, South Korea.
  • Park S; Lunit Inc., Seoul, South Korea.
  • Jia Z; Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China.
  • Chang EI; Microsoft Research, Beijing, China.
  • Xu Y; Microsoft Research, Beijing, China; Biology and Medicine Engineering, Beihang University, Beijing, China.
  • Beck AH; Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
  • van Diest PJ; Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands.
  • Pluim JPW; Medical Image Analysis Group, Eindhoven University of Technology, Eindhoven, the Netherlands.
Med Image Anal ; 54: 111-121, 2019 05.
Article in En | MEDLINE | ID: mdl-30861443
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Image Processing, Computer-Assisted / Breast Neoplasms / Biomarkers, Tumor / Deep Learning Type of study: Guideline / Prognostic_studies / Risk_factors_studies Limits: Female / Humans Language: En Journal: Med Image Anal Journal subject: DIAGNOSTICO POR IMAGEM Year: 2019 Type: Article
Fulltext
Print
XML
PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Image Processing, Computer-Assisted / Breast Neoplasms / Biomarkers, Tumor / Deep Learning Type of study: Guideline / Prognostic_studies / Risk_factors_studies Limits: Female / Humans Language: En Journal: Med Image Anal Journal subject: DIAGNOSTICO POR IMAGEM Year: 2019 Type: Article