Gland segmentation in colon histology images: The glas challenge contest. Sirinukunwattana, K., Pluim, J., P., Chen, H., Qi, X., Heng, P., 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., & Rajpoot, N., M. Medical Image Analysis, 35(1):489-502, 1, 2017. ![Gland segmentation in colon histology images: The glas challenge contest [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website doi abstract bibtex 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.
@article{
title = {Gland segmentation in colon histology images: The glas challenge contest},
type = {article},
year = {2017},
keywords = {Colon cancer,Digital pathology,Histology image analysis,Intestinal gland,Segmentation},
pages = {489-502},
volume = {35},
websites = {https://linkinghub.elsevier.com/retrieve/pii/S1361841516301542},
month = {1},
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created = {2017-12-02T19:49:53.654Z},
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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.},
bibtype = {article},
author = {Sirinukunwattana, Korsuk and Pluim, Josien P.W. and Chen, Hao and Qi, Xiaojuan and Heng, Pheng-Ann and Guo, Yun Bo and Wang, Li Yang and Matuszewski, Bogdan J. and Bruni, Elia and Sanchez, Urko and Böhm, Anton and Ronneberger, Olaf and Cheikh, Bassem Ben and Racoceanu, Daniel and Kainz, Philipp and Pfeiffer, Michael and Urschler, Martin and Snead, David R.J. and Rajpoot, Nasir M.},
doi = {10.1016/j.media.2016.08.008},
journal = {Medical Image Analysis},
number = {1}
}
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