| Literature DB >> 27614792 |
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.
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.Entities:
Keywords: Colon cancer; Digital pathology; Histology image analysis; Intestinal gland; Segmentation
Mesh：
Year: 2016 PMID： 27614792 DOI： 10.1016/j.media.2016.08.008
Source DB: PubMed Journal: Med Image Anal ISSN： 1361-8415 Impact factor: 8.545