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National Repository of Grey Literature 1 records found  Search took 0.00 seconds. 
Deep-learning based segmentation of pathological tissue in brain MR images
 Nantl, Ondřej ; Kolář, Radim (referee) ; Chmelík, Jiří (advisor)
This diploma thesis deals with the topic of segmentation of ischemic tissue in T1 weighted MRI image data using deep learning methods. The theoretical part deals with the anatomy of brain, brain imaging using MRI, available datasets for automatic segmentation of pathological brain tissue and automatic deep learning methods for segmentation of ischemic brain tissue. In the practical part the used dataset and its preprocessing, as well as the proposed deep learning methods (U-Net) and their training, are described. The models were implemented using Python. Finally, the results of the models are presented and discussed.
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