Thesis Details

Hluboké neuronové sítě pro analýzu medicínských obrazových dat

Bachelor's Thesis Student: Szöllösi Albert Academic Year: 2019/2020 Supervisor: Španěl Michal, Ing., Ph.D.
Language
Slovak
Abstract

This thesis offers possible solution to automatic 3D dental scan landmark localization. These scans are used in dental crown design to make the design process easier using specialized software. Before that, though, the scan has to be annotated for the software to know the positions of the teeth. The annotation process is done manually, which guarantees precision, but takes a lot of time. The result of this work could make said process much simpler by applying deep learning. Landmark localization was implemented as heat map regression. Results of the regression were then used to comput the estimated landmark coordinates. 

Keywords

deep learning, medical image data analysis, landmark localization, dental scan

Department
Department of Computer Graphics and Multimedia FIT BUT
Degree Programme
Information Technology
Files
Status
not defended
Date
8 July 2020
Reviewer
Kodym Oldřich, Ing., Ph.D.
Committee
Čadík Martin, doc. Ing., Ph.D. (DCGM FIT BUT), předseda
Bařina David, Ing., Ph.D. (DCGM FIT BUT), člen
Burget Radek, doc. Ing., Ph.D. (DIFS FIT BUT), člen
Holík Lukáš, doc. Mgr., Ph.D. (DITS FIT BUT), člen
Jaroš Jiří, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Citation
SZÖLLÖSI, Albert. Hluboké neuronové sítě pro analýzu medicínských obrazových dat. Brno, 2020. Bachelor's Thesis. Brno University of Technology, Faculty of Information Technology. 2020-07-08. Supervised by Španěl Michal. Available from: https://www-dev.fit.vutbr.cz/study/thesis/22662/
BibTeX 
@bachelorsthesis{FITBT22662,
    author = "Albert Sz{\"{o}}ll{\"{o}}si",
    type = "Bachelor's thesis",
    title = "Hlubok\'{e} neuronov\'{e} s\'{i}t\v{e} pro anal\'{y}zu medic\'{i}nsk\'{y}ch obrazov\'{y}ch dat",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2020,
    location = "Brno, CZ",
    language = "slovak",
    url = "https://www.fit.vut.cz/study/thesis/22662/"
}

Theses

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