Medizinische Universität Graz - Research portal
Selected Publication:
SHR Neuro Cancer Cardio Lipid Metab Microb
Sirinukunwattana, K; Pluim, JPW; Chen, H; Qi, X; Heng, PA; Guo, YB; Wang, LY; Matuszewski, BJ; Bruni, E; Sanchez, U; Böhm, A; Ronneberger, O; Cheikh, BB; Racoceanu, D; Kainz, P; Pfeiffer, M; Urschler, M; Snead, DRJ; Rajpoot, NM.
Gland segmentation in colon histology images: The glas challenge contest.
Med Image Anal. 2017; 35(3):489-502
Doi: 10.1016/j.media.2016.08.008
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- Co-authors Med Uni Graz
- Urschler Martin
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- 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. Copyright © 2016 Elsevier B.V. All rights reserved.
- Find related publications in this database (using NLM MeSH Indexing)
- Algorithms -
- Automation -
- Colonic Neoplasms - diagnostic imaging
- Colonic Neoplasms - pathology
- Datasets as Topic -
- Diagnostic Imaging - methods
- Histological Techniques -
- Humans -
- Reproducibility of Results -
- Find related publications in this database (Keywords)
- Histology image analysis
- Segmentation
- Colon cancer
- Intestinal gland
- Digital pathology