Tools for Automatically Finding and Visualizing Interest Areas in MRI Data to Support Decision Making by Medical Researchers
- Авторы: Fralenko V.P.1, Khachumov M.V.2, Shustova M.V.1
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Учреждения:
- Ailamazyan Program Systems Institute, Russian Academy of Sciences, Yaroslavl Region
- Institute for Systems Analysis, Computer Science and Control Federal Research Center
- Выпуск: Том 44, № 6 (2017)
- Страницы: 397-405
- Раздел: Article
- URL: https://journals.rcsi.science/0147-6882/article/view/175299
- DOI: https://doi.org/10.3103/S0147688217060053
- ID: 175299
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Аннотация
This article gives a detailed description of the techniques developed by the authors for primary and deep processing of magnetic-resonance imaging that are aimed at detecting areas of ischemic lesion in the rat brain. The tools include the techniques for bringing MRI images of different samples to the normalized form (size, shape, and brightness). Another set of tools is associated with the detection of anomalies based on T2 and MDC images using artificial neural networks and specific metrics. It is assumed that the created algorithms and programs will be part of the developed research software system that is oriented to support decision making by medical researchers.
Об авторах
V. Fralenko
Ailamazyan Program Systems Institute, Russian Academy of Sciences, Yaroslavl Region
Автор, ответственный за переписку.
Email: alarmod@pereslavl.ru
Россия, Veskovo Village, 152021
M. Khachumov
Institute for Systems Analysis, Computer Science and Control Federal Research Center
Email: alarmod@pereslavl.ru
Россия, Moscow, 119333
M. Shustova
Ailamazyan Program Systems Institute, Russian Academy of Sciences, Yaroslavl Region
Email: alarmod@pereslavl.ru
Россия, Veskovo Village, 152021
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