Segmentace nádorů mozku v MRI datech s využitím hloubkového učení

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Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií
Abstract
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.
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.
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Citation
USTSINAU, U. Segmentace nádorů mozku v MRI datech s využitím hloubkového učení [online]. Brno: Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. 2020.
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Document version
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en
Study field
Biomedical and Ecological Engineering
Comittee
prof. Ing. Ivo Provazník, Ph.D. (předseda) Ing. Marina Ronzhina, Ph.D. (místopředseda) Ing. Vratislav Harabiš, Ph.D. (člen) Ing. Jan Odstrčilík, Ph.D. (člen) Ing. Jiří Sekora (člen)
Date of acceptance
2020-06-17
Defence
Student prezentoval výsledky své práce a komise byla seznámena s posudky. Student presented the results of his master thesis and the committee members were acquainted with the reviews. Ing. Ronzhina položila otázku, zda student měnil nastavené parametry. Ing. Ronzhina asked if the student tried changing parameters. Prof. Provazník položil otázku, zda je počet pixelů v jednotlivých osách odlišný. Prof. Provazník asked if number of pixels in each of the axes was different. Student defended the master thesis with reservations and answered the questions.
Result of defence
práce byla úspěšně obhájena
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Standardní licenční smlouva - přístup k plnému textu bez omezení
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