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Segmentation of brain tumours in MRI images using deep learning

dc.contributor.advisorChmelík, Jiříen
dc.contributor.authorUstsinau, Usevaladen
dc.date.accessioned2020-06-18T06:59:18Z
dc.date.available2020-06-18T06:59:18Z
dc.date.created2020cs
dc.identifier.citationUSTSINAU, U. Segmentace nádorů mozku v MRI datech s využitím hloubkového učení [online]. Brno: Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. 2020.cs
dc.identifier.other126757cs
dc.identifier.urihttp://hdl.handle.net/11012/189317
dc.description.abstractThe 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.en
dc.description.abstractThe 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.cs
dc.language.isoencs
dc.publisherVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologiícs
dc.rightsStandardní licenční smlouva - přístup k plnému textu bez omezenícs
dc.subjectMedical Imagingen
dc.subjectBrain Tumouren
dc.subjectConvolutional Neural Networken
dc.subjectSegmentationen
dc.subjectU-Neten
dc.subjectMedical Imagingcs
dc.subjectBrain Tumourcs
dc.subjectConvolutional Neural Networkcs
dc.subjectSegmentationcs
dc.subjectU-Netcs
dc.titleSegmentace nádorů mozku v MRI datech s využitím hloubkového učeníen
dc.title.alternativeSegmentation of brain tumours in MRI images using deep learningcs
dc.typeTextcs
dcterms.dateAccepted2020-06-17cs
dcterms.modified2020-06-17-13:18:29cs
thesis.disciplineBiomedical and Ecological Engineeringcs
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav biomedicínského inženýrstvícs
thesis.levelInženýrskýcs
thesis.nameIng.cs
sync.item.dbid126757en
sync.item.dbtypeZPen
sync.item.insts2020.06.18 08:59:18en
sync.item.modts2020.06.18 08:17:33en
eprints.affiliatedInstitution.facultyFakulta elektrotechniky a komunikačních technologiícs
dc.contributor.refereeOdstrčilík, Janen
dc.description.markDcs
dc.type.drivermasterThesisen
dc.type.evskpdiplomová prácecs
but.committeeprof. 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)cs
but.defenceStudent 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.cs
but.resultpráce byla úspěšně obhájenacs
but.programElectrical, Electronic, Communication and Control Technologycs
but.jazykangličtina (English)


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