COMPARATIVE FEATURES OF OPEN SOURCE SOFTWARE PRODUCTS FOR THE DEVELOPMENT OF AN AUTOMATED BREAST CANCER DIAGNOSTIC PROGRAM

Kovalev V.; Diachenko Y.; Malyshev V.; Rjabceva S.; Kolomiets O.; Lyndin M.; Moskalenko R.; Dovbysh A.; Romaniuk A.

Kovalev V. Biomedical Image Analysis Department of United Institute of Informatics Problem Belarus National Academy of Sciences, Minsk, Belarus
Diachenko Y. Laboratory “Center of electron and light microscopy” Institute of Physiology of the National Academy of Sciences of Belarus, Minsk, Belarus
Malyshev V. Biomedical Image Analysis Department of United Institute of Informatics Problem Belarus National Academy of Sciences, Minsk, Belarus
Rjabceva S. Department of Computer Sciences of Sumy State University, Sumy, Ukraine
Kolomiets O. Department of Pathology of Sumy State University, Sumy, Ukraine
Lyndin M. Department of Pathology of Sumy State University, Sumy, Ukraine
Moskalenko R. Department of Pathology of Sumy State University, Sumy, Ukraine
Dovbysh A. Laboratory “Center of electron and light microscopy” Institute of Physiology of the National Academy of Sciences of Belarus, Minsk, Belarus
Romaniuk A. Department of Pathology of Sumy State University, Sumy, Ukraine

Keywords: breast cancer, digital pathology, whole-slide image, histopathological diagnosis, automated diagnostic program

Abstract

Breast cancer is one of the most common cancer diseases in the world among women. The reliability of histological verification of breast cancer depends on pathologist’s experience, knowledge, his willingness to self-improve and study specialized literature. Digital pathology is also widely used for educational purposes, in telepathology, teleconsultation and research projects. Recently developed Whole Slide Image (WSI) system opens great opportunities in the histopathological diagnosis quality improvement. Digital whole-slide images provide the effective use of morphometry and various imaging techniques to assist pathologists in quantitative and qualitative evaluation of histopathological preparations. The development of software for morphological diagnosis is important for improving the quality of histological verification of diagnosis in oncopathology. The purpose of this work is to find and benchmark existing open-source software for the whole-slide histological images processing. Choosing an open source program is an important step in developing an automated breast cancer diagnosis program.

The result is a detailed study of open-source software: ASAP, Orbit, Cytomine and QuPath. Their features and methods of image processing were analyzed. QuPath software has the best characteristics for extending it with an automated module for the cancer diagnosis. QuPath combines a user-friendly, easy-to-use interface, customizable functionality, and moderate computing power requirements. Besides, QuPath works with whole-slide images with immunohistochemical markers; features implemented in this software allow making a morphometric analysis.

QuPath saves time for a graphical user interface development and provides a scalable system to add new key features. QuPath supports third-party MATLAB and Python extensions.

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