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Segmentace nádorů mozku v MRI datech s využitím hloubkového učení / Segmentation of brain tumours in MRI images using deep learning

The following master's thesis paper equipped with a short description of CT scans and MR images and the main differences between them, explanation of the structure of convolutional neural networks and how they implemented into biomedical image analysis, besides it was taken a popular modification of U-Net and tested on two loss-functions. As far as segmentation quality plays a highly important role for doctors, in experiment part it was paid significant attention to training quality and prediction results of the model. The experiment has shown the effectiveness of the provided algorithm and performed 100 training cases with the following analysis through the similarity. The proposed outcome gives us certain ideas for future improving the quality of image segmentation via deep learning techniques.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:413176
Date January 2020
CreatorsUstsinau, Usevalad
ContributorsOdstrčilík, Jan, Chmelík, Jiří
PublisherVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií
Source SetsCzech ETDs
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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