Original title: Segmentace nádorů mozku v MRI datech s využitím hloubkového učení
Translated title: Segmentation of brain tumours in MRI images using deep learning
Authors: Ustsinau, Usevalad ; Odstrčilík, Jan (referee) ; Chmelík, Jiří (advisor)
Document type: Master’s theses
Year: 2020
Language: eng
Publisher: 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.
Keywords: Brain Tumour; Convolutional Neural Network; Medical Imaging; Segmentation; U-Net; Brain Tumour; Convolutional Neural Network; Medical Imaging; Segmentation; U-Net

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/189317

Permalink: http://www.nusl.cz/ntk/nusl-413176


The record appears in these collections:
Universities and colleges > Public universities > Brno University of Technology
Academic theses (ETDs) > Master’s theses