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Gland segmentation in colon histology images: The glas challenge contest

K. Sirinukunwattana, J. Pluim, H. Chen, X. Qi, P. Heng, Y. Guo, L. Wang, B. Matuszewski, E. Bruni, U. Sanchez, Anton Böhm, Olaf Ronneberger, B. Cheikh, D. Racoceanu, P. Kainz, M. Pfeiffer, M. Urschler, D. Snead, N. Rajpoot
Medical Image Analysis, 35: 489-502, 2017
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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@Article{BR17,
  author       = "K. Sirinukunwattana and JPW. Pluim and H. Chen and X. Qi and PA. Heng and YB. Guo and LY. Wang and BJ. Matuszewski and E. Bruni and U. Sanchez and A. B{\"o}hm and O. Ronneberger and BB. Cheikh and D. Racoceanu and P. Kainz and M. Pfeiffer and M. Urschler and DRJ. Snead and NM. Rajpoot",
  title        = "Gland segmentation in colon histology images: The glas challenge contest",
  journal      = "Medical Image Analysis",
  volume       = "35",
  pages        = "489-502",
  month        = " ",
  year         = "2017",
  url          = "http://lmb.informatik.uni-freiburg.de/Publications/2017/BR17"
}

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