Development of neoplastic region selection algorithm based on breast cancer whole slide image
https://doi.org/10.35596/1729-7648-2020-18-8-21-28
Abstract
Analysis of breast cancer whole-slide image is an extremely labor-intensive process. Histological whole slide images have the following features: a high degree of tissue diversity both in one image and between different images, hierarchy, a large amount of graphic information and different artifacts. In this work, pre-processing of breast cancer whole-slide tissue image was carried out, which included normalization of the color distribution and the image area selection. We reduced the operating time of the other algorithms and excluded areas of breast cancer whole-slide tissue with a background to analyze. Also, an algorithm for finding similar neoplastic regions for semi-automatic selection using various image descriptors has been developed and implemented.
Supporting agencies: The work was carried out as part of the assignment of joint Belarusian-Ukrainian projects of State Committee for Science and Technology “To develop an automated program for breast cancer differential diagnosis with morphometric assessment of cancer cells receptor status” with the support of the Belarusian Foundation for Basic Research.
About the Authors
S. N. Rjabceva
Institute of Physiology of National Academy of Sciences of Belarus
Belarus
Belarus
Rjabceva S.N., PhD, the Head of Laboratory “Center of Electron and Light Microscopy”
220072, Republic of Belarus Minsk, Academicheskaya str., 28
V. A. Kovalev
United Institute of Informatics Problem of National Academy of Sciences of Belarus
Belarus
Belarus
Kovalev V.A., PhD, the Head of Laboratory “Biomedical Image Analysis”
Minsk
V. D. Malyshev
United Institute of Informatics Problem of National Academy of Sciences of Belarus
Belarus
Belarus
Malyshev V.D., Software Engineer of Laboratory “Biomedical Image Analysis”
Minsk
I. A. Siamionik
Institute of Physiology of National Academy of Sciences of Belarus
Belarus
Belarus
Siamionik I.A., PhD, Senior Researcher of Laboratory “Center of Electron and Light Microscopy”
Minsk
M. A. Derevyanko
Institute of Physiology of National Academy of Sciences of Belarus
Belarus
Belarus
Derevyanko M.A., PhD, Senior Researcher of Laboratory “Center of Electron and Light Microscopy”
Minsk
R. A. Moskalenko
Sumy State University
Ukraine
Moskalenko R.A., D.Sci, Associate Professor of the Pathological Anatomy Department
Ukraine
Moskalenko R.A., D.Sci, Associate Professor of the Pathological Anatomy Department
A. S. Dovbysh
Sumy State University
Ukraine
Dovbysh A.S., D.Sci, Professor Professor of the Computer Sciences Department
Ukraine
Dovbysh A.S., D.Sci, Professor Professor of the Computer Sciences Department
T. R. Savchenko
Sumy State University
Ukraine
Savchenko T.R., Student of the Computer Sciences Department
Ukraine
Savchenko T.R., Student of the Computer Sciences Department
A. N. Romaniuk
Sumy State University
Ukraine
Romaniuk A.N., D.Sci, Professor of the Pathological Anatomy Department
Ukraine
Romaniuk A.N., D.Sci, Professor of the Pathological Anatomy Department
References
1. Dimitriou N., Arandjelovic O., Caie P.D. Deep Learning for Whole Slide Image Analysis: An Overview. Frontiers of Medicine. October 19, 2019;1-11. https://www.researchgate.net/publication/336671999.
2. DICOM Whole Slide Imaging. – URL:http://dicom.nema.org/Dicom/DICOMWSI/ (дата обращения 21.10.2020).
3. Macenko M., Niethammer M., Marron J. S., Borland D., Woosley J. T., Guan X., Schmitt C., Thomas N. E. A method for normalizing histology slides for quantitative analysis. In IEEE International Symposium on Biomedical Imaging: From Nano to Macro. 2009;1107-1110. DOI: 10.1109/ISBI.2009.5193250.
4. Bankhead P., Loughrey M. B., Fernández J.A., Dombrowski Y., McArt D.G., Dunne P.D., McQuaid S., Gray R.T., Murray L.J., Coleman H.G., James J.A., Salto-Tellez M., Hamilton P.W. QuPath: Open source software for digital pathology image analysis. Scientific Reports. 2017;7(1):168-78. DOI:10.1038/s41598- 017-17204-5.
Review
For citations:
Rjabceva S.N., Kovalev V.A., Malyshev V.D., Siamionik I.A., Derevyanko M.A., Moskalenko R.A., Dovbysh A.S., Savchenko T.R., Romaniuk A.N. Development of neoplastic region selection algorithm based on breast cancer whole slide image. Doklady BGUIR. 2020;18(8):21-28. (In Russ.) https://doi.org/10.35596/1729-7648-2020-18-8-21-28
Views: 3657
Email this article 