Gland segmentation in colon histology images: The glas challenge contest

Korsuk Sirinukunwattana; J.P.W. 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, J.P.W. 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

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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.

Originele taal-2	Engels
Pagina's (van-tot)	489-502
Aantal pagina's	14
Tijdschrift	Medical Image Analysis
Volume	35
DOI's	https://doi.org/10.1016/j.media.2016.08.008
Status	Gepubliceerd - 3 sep. 2016

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Sirinukunwattana, K., Pluim, J. P. W., 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. (2016). 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{273e63c68226423980f8d77e1d54a288,

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{\textquoteright}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 J.P.W. Pluim and Hao Chen and Xiaojuan Qi and Heng, {Pheng Ann} 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.}",

year = "2016",

month = sep,

day = "3",

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, PA, 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 2016, 'Gland segmentation in colon histology images: The glas challenge contest', Medical Image Analysis, vol. 35, blz. 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, J.P.W.

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 - 2016/9/3

Y1 - 2016/9/3

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.

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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

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