Gland segmentation in colon histology images: The glas challenge contest.
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.
Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK. Electronic address: k.sirinukunwattana@warwick.ac.uk.
Korsuk
K
Sirinukunwattana
Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.
Josien P W
JPW
Pluim
Department of Computer Science and Engineering, The Chinese University of Hong Kong, China.
Hao
H
Chen
Department of Computer Science and Engineering, The Chinese University of Hong Kong, China.
Xiaojuan
X
Qi
Department of Computer Science and Engineering, The Chinese University of Hong Kong, China.
Pheng-Ann
PA
Heng
School of Engineering, University of Central Lancashire, Preston, UK.
Yun Bo
YB
Guo
School of Engineering, University of Central Lancashire, Preston, UK.
Li Yang
LY
Wang
School of Engineering, University of Central Lancashire, Preston, UK.
Bogdan J
BJ
Matuszewski
ExB Research and Development, Germany.
Elia
E
Bruni
ExB Research and Development, Germany.
Urko
U
Sanchez
Computer Science Department, University of Freiburg, Germany.
Anton
A
Böhm
Computer Science Department, University of Freiburg, Germany; BIOSS Centre for Biological Signalling Studies, University of Freiburg, Germany and Google-DeepMind, London, UK.
Olaf
O
Ronneberger
Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Biomedical Imaging Laboratory (LIB), Paris, France.
Bassem Ben
BB
Cheikh
Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Biomedical Imaging Laboratory (LIB), Paris, France.
Daniel
D
Racoceanu
Institute of Biophysics, Center for Physiological Medicine, Medical University of Graz, Graz, Austria; Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
Philipp
P
Kainz
Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
Michael
M
Pfeiffer
Institute for Computer Graphics and Vision, BioTechMed, Graz University of Technology, Graz, Austria; Ludwig Boltzmann Institute for Clinical Forensic Imaging, Graz, Austria.
Martin
M
Urschler
Department of Pathology, University Hospitals Coventry and Warwickshire, Walsgrave, Coventry, CV2 2DX, UK.
David R J
DRJ
Snead
Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK. Electronic address: n.m.rajpoot@warwick.ac.uk.
Nasir M
NM
Rajpoot
D000465:Algorithms; D001331:Automation; D003110:Colonic Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology*; D066264:Datasets as Topic; D003952:Diagnostic Imaging / Q000379:methods*; D006652:Histological Techniques; D006801:Humans; D015203:Reproducibility of Results
Colon cancer; Digital pathology; Histology image analysis; Intestinal gland; Segmentation