Gland segmentation in colon histology images: The glas challenge contest

Korsuk Sirinukunwattana; Josien 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

Med Image Anal. 2017 Jan:35:489-502. doi: 10.1016/j.media.2016.08.008. Epub 2016 Sep 3.

Authors

Korsuk Sirinukunwattana¹, Josien P W Pluim², Hao Chen³, Xiaojuan Qi³, Pheng-Ann Heng³, Yun Bo Guo⁴, Li Yang Wang⁴, Bogdan J Matuszewski⁴, Elia Bruni⁵, Urko Sanchez⁵, Anton Böhm⁶, Olaf Ronneberger⁷, Bassem Ben Cheikh⁸, Daniel Racoceanu⁸, Philipp Kainz⁹, Michael Pfeiffer¹⁰, Martin Urschler¹¹, David R J Snead¹², Nasir M Rajpoot¹³

Affiliations

¹ Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK. Electronic address: k.sirinukunwattana@warwick.ac.uk.
² Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.
³ Department of Computer Science and Engineering, The Chinese University of Hong Kong, China.
⁴ School of Engineering, University of Central Lancashire, Preston, UK.
⁵ ExB Research and Development, Germany.
⁶ Computer Science Department, University of Freiburg, Germany.
⁷ Computer Science Department, University of Freiburg, Germany; BIOSS Centre for Biological Signalling Studies, University of Freiburg, Germany and Google-DeepMind, London, UK.
⁸ Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Biomedical Imaging Laboratory (LIB), Paris, France.
⁹ Institute of Biophysics, Center for Physiological Medicine, Medical University of Graz, Graz, Austria; Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
¹⁰ Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
¹¹ Institute for Computer Graphics and Vision, BioTechMed, Graz University of Technology, Graz, Austria; Ludwig Boltzmann Institute for Clinical Forensic Imaging, Graz, Austria.
¹² Department of Pathology, University Hospitals Coventry and Warwickshire, Walsgrave, Coventry, CV2 2DX, UK.
¹³ Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK. Electronic address: n.m.rajpoot@warwick.ac.uk.

PMID: 27614792
DOI: 10.1016/j.media.2016.08.008

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.

Keywords: Colon cancer; Digital pathology; Histology image analysis; Intestinal gland; Segmentation.

Publication types

Review

MeSH terms

Algorithms*
Automation
Colonic Neoplasms / diagnostic imaging*
Colonic Neoplasms / pathology*
Datasets as Topic
Diagnostic Imaging / methods*
Histological Techniques*
Humans
Reproducibility of Results