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Gland segmentation in colon histology images: The glas challenge contest.
Sirinukunwattana, Korsuk; Pluim, Josien P W; Chen, Hao; Qi, Xiaojuan; Heng, Pheng-Ann; Guo, Yun Bo; Wang, Li Yang; Matuszewski, Bogdan J; Bruni, Elia; Sanchez, Urko; Böhm, Anton; Ronneberger, Olaf; Cheikh, Bassem Ben; Racoceanu, Daniel; Kainz, Philipp; Pfeiffer, Michael; Urschler, Martin; Snead, David R J; Rajpoot, Nasir M.
Afiliação
  • Sirinukunwattana K; Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK. Electronic address: k.sirinukunwattana@warwick.ac.uk.
  • Pluim JPW; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.
  • Chen H; Department of Computer Science and Engineering, The Chinese University of Hong Kong, China.
  • Qi X; Department of Computer Science and Engineering, The Chinese University of Hong Kong, China.
  • Heng PA; Department of Computer Science and Engineering, The Chinese University of Hong Kong, China.
  • Guo YB; School of Engineering, University of Central Lancashire, Preston, UK.
  • Wang LY; School of Engineering, University of Central Lancashire, Preston, UK.
  • Matuszewski BJ; School of Engineering, University of Central Lancashire, Preston, UK.
  • Bruni E; ExB Research and Development, Germany.
  • Sanchez U; ExB Research and Development, Germany.
  • Böhm A; Computer Science Department, University of Freiburg, Germany.
  • Ronneberger O; Computer Science Department, University of Freiburg, Germany; BIOSS Centre for Biological Signalling Studies, University of Freiburg, Germany and Google-DeepMind, London, UK.
  • Cheikh BB; Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Biomedical Imaging Laboratory (LIB), Paris, France.
  • Racoceanu D; Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Biomedical Imaging Laboratory (LIB), Paris, France.
  • Kainz P; Institute of Biophysics, Center for Physiological Medicine, Medical University of Graz, Graz, Austria; Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
  • Pfeiffer M; Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
  • Urschler M; Institute for Computer Graphics and Vision, BioTechMed, Graz University of Technology, Graz, Austria; Ludwig Boltzmann Institute for Clinical Forensic Imaging, Graz, Austria.
  • Snead DRJ; Department of Pathology, University Hospitals Coventry and Warwickshire, Walsgrave, Coventry, CV2 2DX, UK.
  • Rajpoot NM; Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK. Electronic address: n.m.rajpoot@warwick.ac.uk.
Med Image Anal ; 35: 489-502, 2017 01.
Article em En | MEDLINE | ID: mdl-27614792
ABSTRACT
Colorectal adenocarcinoma originating in intestinal glandular structures is the most common form of colon cancer. In clinical practice, the morphology of intestinal glands, including architectural appearance and glandular formation, is used by pathologists to inform prognosis and plan the treatment of individual patients. However, achieving good inter-observer as well as intra-observer reproducibility of cancer grading is still a major challenge in modern pathology. An automated approach which quantifies the morphology of glands is a solution to the problem. This paper provides an overview to the Gland Segmentation in Colon Histology Images Challenge Contest (GlaS) held at MICCAI'2015. Details of the challenge, including organization, dataset and evaluation criteria, are presented, along with the method descriptions and evaluation results from the top performing methods.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Diagnóstico por Imagem / Técnicas Histológicas / Neoplasias do Colo Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Med Image Anal Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2017 Tipo de documento: Article
Texto completo
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Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Diagnóstico por Imagem / Técnicas Histológicas / Neoplasias do Colo Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Med Image Anal Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2017 Tipo de documento: Article