TY - JOUR
T1 - Gland segmentation in colon histology images
T2 - The glas challenge contest
AU - Sirinukunwattana, Korsuk
AU - Pluim, Josien 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.
N1 - Publisher Copyright:
© 2016 Elsevier B.V.
PY - 2017/1/1
Y1 - 2017/1/1
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.
KW - Colon cancer
KW - Digital pathology
KW - Histology image analysis
KW - Intestinal gland
KW - Segmentation
UR - http://www.scopus.com/inward/record.url?scp=84994310706&partnerID=8YFLogxK
U2 - 10.1016/j.media.2016.08.008
DO - 10.1016/j.media.2016.08.008
M3 - Article
C2 - 27614792
AN - SCOPUS:84994310706
SN - 1361-8415
VL - 35
SP - 489
EP - 502
JO - Medical Image Analysis
JF - Medical Image Analysis
ER -