AUTOMATIC MUCOUS GLANDS SEGMENTATION IN HISTOLOGICAL IMAGES

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Khvostikov, A.^1¹  Krylov, A.^1² 

[1] Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Moscow, Russia^1;University Medical Center, Lomonosov Moscow State University, Moscow, Russia^2

关键词: Image segmentation;    Mucous glands;    Deep Learning;    Convolutional Neural Networks;    Histology;    Pathology;   

DOI  :  10.5194/isprs-archives-XLII-2-W12-103-2019

学科分类：地球科学(综合)

来源: Copernicus Publications

【 摘 要 】

Mucous glands is an important diagnostic element in digestive pathology. The first step of differential diagnosis of colon polyps in order to assess their malignant potential is gland segmentation. The process of mucous glands segmentation is challenging as the glands not only needed to be separated from a background but also individually identified to obtain reliable morphometric criteria for quantitative diagnostic methods. We propose a new convolutional neural network for mucous gland segmentation that takes into account glands’ contours and can be used for gland instance segmentation. Training and evaluation of the network was performed on a standard Warwick-QU dataset as well as on the collected PATH-DT-MSU dataset of histological images obtained from hematoxylin and eosin staining of paraffin sections of colon biopsy material collected by our Pathology department. The collected PATH-DT-MSU dataset will be available at http://imaging.cs.msu.ru/en/research/histology.

【 授权许可】

CC BY