Thesis Details

Hluboké neuronové sítě pro analýzu medicínských obrazových dat

Bachelor's Thesis Student: Bíl Tomáš Academic Year: 2018/2019 Supervisor: Španěl Michal, doc. Ing., Ph.D.
English title
Deep Learning for Medical Image Analysis
Language
Czech
Abstract

The goal of this thesis is developing convolutional neural network which is able to classify if x-ray images are suitable for cephalometry analysis. Four networks were created and trained on a dataset for this purpose. Two of them are VGG type, one is based on UNet and one is Resnet. The dataset was generated from ct scan images. VGG network with four blocks has got the best results.  Measured accuracy performed on test dataset is 97%.

Keywords

machine learning, Artificial Neural Network, cephalometry, image recognition

Department
Department of Computer Graphics and Multimedia FIT BUT
Degree Programme
Information Technology
Files
Status
defended, grade C
Date
11 June 2019
Reviewer
Kodym Oldřich, Ing., Ph.D.
Committee
Herout Adam, prof. Ing., Ph.D. (DCGM FIT BUT), předseda
Bidlo Michal, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Čadík Martin, doc. Ing., Ph.D. (DCGM FIT BUT), člen
Křivka Zbyněk, Ing., Ph.D. (DIFS FIT BUT), člen
Rogalewicz Adam, doc. Mgr., Ph.D. (DITS FIT BUT), člen
Citation
BÍL, Tomáš. Hluboké neuronové sítě pro analýzu medicínských obrazových dat. Brno, 2019. Bachelor's Thesis. Brno University of Technology, Faculty of Information Technology. 2019-06-11. Supervised by Španěl Michal. Available from: https://www-dev.fit.vutbr.cz/study/thesis/22018/
BibTeX 
@bachelorsthesis{FITBT22018,
    author = "Tom\'{a}\v{s} B\'{i}l",
    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 = 2019,
    location = "Brno, CZ",
    language = "czech",
    url = "https://www.fit.vut.cz/study/thesis/22018/"
}

Theses

Back to top