Gland segmentation in colon histology images: The glas challenge contest

Korsuk Sirinukunwattana; JPW Pluim; Hao Chen; Xiaojuan Qi; Pheng-Ann Heng; Yun Bo Guo; Li Yang Wang; Bogdan J Matuszewski; Elia Bruni; Urko Sanchez; Anton Böhm; Olaf Ronneberger; Bassem Ben Cheikh; Daniel Racoceanu; Philipp Kainz; Michael Pfeiffer; Martin Urschler; David R J Snead; Nasir M Rajpoot

doi:10.1016/j.media.2016.08.008

Gland segmentation in colon histology images: The glas challenge contest

Korsuk Sirinukunwattana, JPW Pluim, Hao Chen, Xiaojuan Qi, Pheng-Ann Heng, Yun Bo Guo, Li Yang Wang, Bogdan J Matuszewski, Elia Bruni, Urko Sanchez, Anton Böhm, Olaf Ronneberger, Bassem Ben Cheikh, Daniel Racoceanu, Philipp Kainz, Michael Pfeiffer, Martin Urschler, David R J Snead, Nasir M Rajpoot

Research output: Contribution to journal › Article › Academic › peer-review

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.

Original language	English
Pages (from-to)	489-502
Number of pages	14
Journal	Medical Image Analysis
Volume	35
DOIs	https://doi.org/10.1016/j.media.2016.08.008
Publication status	Published - Jan 2017
Externally published	Yes

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Sirinukunwattana, K., Pluim, JPW., Chen, H., Qi, X., Heng, P.-A., Guo, Y. B., Wang, L. Y., Matuszewski, B. J., Bruni, E., Sanchez, U., Böhm, A., Ronneberger, O., Cheikh, B. B., Racoceanu, D., Kainz, P., Pfeiffer, M., Urschler, M., Snead, D. R. J., & Rajpoot, N. M. (2017). Gland segmentation in colon histology images: The glas challenge contest. Medical Image Analysis, 35, 489-502. https://doi.org/10.1016/j.media.2016.08.008

@article{b4ae6a537ec94a0a9da87619941a416f,

title = "Gland segmentation in colon histology images: The glas challenge contest",

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.",

author = "Korsuk Sirinukunwattana and JPW Pluim and Hao Chen and Xiaojuan Qi and Pheng-Ann Heng and Guo, {Yun Bo} and Wang, {Li Yang} and Matuszewski, {Bogdan J} and Elia Bruni and Urko Sanchez and Anton B{\"o}hm and Olaf Ronneberger and Cheikh, {Bassem Ben} and Daniel Racoceanu and Philipp Kainz and Michael Pfeiffer and Martin Urschler and Snead, {David R J} and Rajpoot, {Nasir M}",

note = "Publisher Copyright: {\textcopyright} 2016 Elsevier B.V.",

year = "2017",

month = jan,

doi = "10.1016/j.media.2016.08.008",

language = "English",

volume = "35",

pages = "489--502",

journal = "Medical Image Analysis",

issn = "1361-8415",

publisher = "Elsevier",

}

Sirinukunwattana, K, Pluim, JPW, Chen, H, Qi, X, Heng, P-A, Guo, YB, Wang, LY, Matuszewski, BJ, Bruni, E, Sanchez, U, Böhm, A, Ronneberger, O, Cheikh, BB, Racoceanu, D, Kainz, P, Pfeiffer, M, Urschler, M, Snead, DRJ & Rajpoot, NM 2017, 'Gland segmentation in colon histology images: The glas challenge contest', Medical Image Analysis, vol. 35, pp. 489-502. https://doi.org/10.1016/j.media.2016.08.008

TY - JOUR

T1 - Gland segmentation in colon histology images

T2 - The glas challenge contest

AU - Sirinukunwattana, Korsuk

AU - Pluim, JPW

AU - Chen, Hao

AU - Qi, Xiaojuan

AU - Heng, Pheng-Ann

AU - Guo, Yun Bo

AU - Wang, Li Yang

AU - Matuszewski, Bogdan J

AU - Bruni, Elia

AU - Sanchez, Urko

AU - Böhm, Anton

AU - Ronneberger, Olaf

AU - Cheikh, Bassem Ben

AU - Racoceanu, Daniel

AU - Kainz, Philipp

AU - Pfeiffer, Michael

AU - Urschler, Martin

AU - Snead, David R J

AU - Rajpoot, Nasir M

PY - 2017/1

Y1 - 2017/1

N2 - 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.

AB - 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.

U2 - 10.1016/j.media.2016.08.008

DO - 10.1016/j.media.2016.08.008

M3 - Article

C2 - 27614792

SN - 1361-8415

VL - 35

SP - 489

EP - 502

JO - Medical Image Analysis

JF - Medical Image Analysis

ER -

Gland segmentation in colon histology images: The glas challenge contest

Abstract

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