Histological Images Processing and Analysis

This page is devoted to our research on different problems of histological images processing and analysis.

Our research is focused on developing algorithms for:

  • semantic segmentation of mucous glands in histological images;
  • instance segmentation of mucous glands in histological images;
  • hybrid approach of instance gland segmentation.

Datasets

PATH-DT-MSU

In our research we use PATH-DT-MSU dataset, that was collected and prepared by Laboratory of Mathematical Methods of Image Processing, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University and Department of Pathology, Medical Research and Educational Center (University Clinic), Lomonosov Moscow State University.

sample image from S1 set visualization of corresponding gland and "open" gland annotations from S1 set preview of whole slide image from WSS1 with visualization of annotation

PathScribe project

PathScribe is a multi-platform client-server application that allows to efficiently work with whole slide images of any size without having to download them to your device. PathScribe implements an adaptive and modern interface that allows to comfortably work with histological images, both on a desktop computer or laptop, and on mobile devices (tablets, smartphones) with touch screens.

Website: https://pathscribe.ru/

Our team

Alexander Khvostikov
khvostikov@cs.msu.ru
ORCID: 0000-0002-4217-7141
Laboratory of Mathematical Methods of Image Processing, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University

Andrey Krylov
kryl@cs.msu.ru
ORCID: 0000-0001-9910-4501
Professor, Head of the Laboratory of Mathematical Methods of Image Processing, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University

Ilya Mikhailov
imihailov@mc.msu.ru
ORCID: 0000-0001-8020-369X
Trainee researcher, Department of Pathology, Medical Research and Educational Center, Lomonosov Moscow State University.

Nina Oleynikova
noleynikova@mc.msu.ru
ORCID: 0000-0001-8564-8874
MD, PhD, Researcher scientist, Department of Pathology, Medical Research and Educational Center, Lomonosov Moscow State University.

Olga Kharlova
olga.arsenteva@gmail.com
ORCID: 0000-0002-5909-1248
MD, PhD

Natalia Danilova
ndanilova@mc.msu.ru
ORCID: 0000-0001-7848-6707
MD, PhD, Senior researcher scientist, Department of Pathology, Medical Research and Educational Center, Lomonosov Moscow State University.

Pavel Malkov
pmalkov@mc.msu.ru
ORCID: 0000-0001-5074-3513
MD, ScD, Head of Department of Pathology, Medical Research and Educational Center, Lomonosov Moscow State University.

Acknowledgement

The work was supported by Russian Science Foundation grant 17-11-01279.

Bibliography

2019

A. Khvostikov, A. Krylov, I. Mikhailov, O. Kharlova, N. Oleynikova, P. Malkov. “Automatic mucous glands segmentation in histological images” // In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLII-2/W12. 2019, pp. 103−109. Link.

N. Oleynikova, A. Khvostikov, A. Krylov, I. Mikhailov, O. Kharlova, N. Danilova, P. Malkov, N. Ageykina, E. Fedorov. “Automatic glands segmentation in histological images obtained by endoscopic biopsy from various parts of the colon” // Endoscopy, Vol. 51(04), 2019, pp. 6−7. Link.

2018

A. Khvostikov, A. S. Krylov, O. Kharlova, N. Oleynikova, I. Mikhailov, P. Malkov. “CNN-based histological images segmentation of mucous glands” // Proceedings of the 28th International Conference on Computer Graphics and Vision GraphiCon'2018, Россия, Томск, 2018, pp. 258−261.