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Proceedings Paper

A structure-based approach for colon gland segmentation in digital pathology
Author(s): Bassem Ben Cheikh ; Philippe Bertheau; Daniel Racoceanu
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Paper Abstract

The morphology of intestinal glands is an important and significant indicator of the level of the severity of an inflammatory bowel disease, and has also been used routinely by pathologists to evaluate the malignancy and the prognosis of colorectal cancers such as adenocarcinomas. The extraction of meaningful information describing the morphology of glands relies on an accurate segmentation method. In this work, we propose a novel technique based on mathematical morphology that characterizes the spatial positioning of nuclei for intestinal gland segmentation in histopathological images. According to their appearance, glands can be divided into two types: hallow glands and solid glands. Hallow glands are composed of lumen and/or goblet cells cytoplasm, or filled with abscess in some advanced stages of the disease, while solid glands are composed of bunches of cells clustered together and can also be filled with necrotic debris. Given this scheme, an efficient characterization of the spatial distribution of cells is sufficient to carry out the segmentation. In this approach, hallow glands are first identified as regions empty of nuclei and surrounded by thick layers of epithelial cells, then solid glands are identified by detecting regions crowded of nuclei. First, cell nuclei are identified by color classification. Then, morphological maps are generated by the mean of advanced morphological operators applied to nuclei objects in order to interpret their spatial distribution and properties to identify candidates for glands central-regions and epithelial layers that are combined to extract the glandular structures.

Paper Details

Date Published: 23 March 2016
PDF: 8 pages
Proc. SPIE 9791, Medical Imaging 2016: Digital Pathology, 97910J (23 March 2016); doi: 10.1117/12.2216545
Show Author Affiliations
Bassem Ben Cheikh , UPMC Sorbonne Univ., CNRS, INSERM, Biomedical Imaging Lab. (France)
Philippe Bertheau, Univ. Paris Diderot, USPC, APHP, Hôpital Saint-Louis (France)
Daniel Racoceanu, UPMC Sorbonne Univ., CNRS, INSERM, Biomedical Imaging Lab. (France)


Published in SPIE Proceedings Vol. 9791:
Medical Imaging 2016: Digital Pathology
Metin N. Gurcan; Anant Madabhushi, Editor(s)

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