Computerized diagnosis of prostate cancer based on whole slide histology images and deep learning methods
This paper presents the results of an experimental study and the development of tools for automatic analysis and recognition of histological images in order to obtain quantitative estimates of the presence and degree of aggressiveness of prostate cancer in the commonly used Gleason and ISUP scales....
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| Main Authors: | V. A. Kovalev, D. M. Voynov, V. D. Malyshau, E. D. Lapo |
|---|---|
| Format: | Article |
| Language: | Russian |
| Published: |
National Academy of Sciences of Belarus, the United Institute of Informatics Problems
2021-01-01
|
| Series: | Informatika |
| Subjects: | |
| Online Access: | https://inf.grid.by/jour/article/view/1090 |
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