Title
Gland segmentation in colon histology images: The glas challenge contest
Date Issued
01 January 2017
Access level
open access
Resource Type
journal article
Author(s)
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.
Kainz P.
Pfeiffer M.
Urschler M.
Snead D.R.J.
Rajpoot N.M.
Sorbonne Universités
Publisher(s)
Elsevier B.V.
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.
Start page
489
End page
502
Volume
35
Language
English
OCDE Knowledge area
Ciencias de la computación
Radiología, Medicina nuclear, Imágenes médicas
Gastroenterología, Hepatología
Subjects
Scopus EID
2-s2.0-84994310706
PubMed ID
Source
Medical Image Analysis
ISSN of the container
13618415
Sponsor(s)
This paper was made possible by NPRP grant number NPRP5-1345-1-228 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. Korsuk Sirinukunwattana acknowledges the partial financial support provided by the Department of Computer Science, University of Warwick, UK. CUMedVision team acknowledges Hong Kong RGC General Research Fund (Project No. CUHK 412513). The work of Olaf Ronneberger was supported by the Excellence Initiative of the German Federal and State Governments (EXC 294). Philipp Kainz was supported by the Excellence Grant 2014 of the Federation of Austrian Industries (IV), and Martin Urschler acknowledges funding by the Austrian Science Fund (FWF): P 28078-N33 .
Sources of information:
Directorio de Producción Científica
Scopus