Thesis Details

Hluboké neuronové sítě pro analýzu medicínských obrazových dat

Bachelor's Thesis Student: Trávníčková Kateřina Academic Year: 2016/2017 Supervisor: Španěl Michal, Ing., Ph.D.
English title
Deep Learning for Medical Image Analysis
Language
Czech
Abstract

This bachelor thesis deals with medical volume data analysis using convolutional neural networks. The input of the analysis is a CT scan of human limbs and the output are segmented countours of long bones, humerus and tibia. The goal of this work is to find suitable convolutional neural network settings to achieve the best possible analysis output while the area under the Precision-Recall curve is used as the precision metric. The best accuracy reaches almost 88 % (0.8778 AUC). The implementation is based on Caffe framework, or python caffe module.

Keywords

Convolution, convolutional neural networks, machine learning, object contour segmentation, medical volume data, Caffe framework, pycaffe

Department
Department of Computer Graphics and Multimedia FIT BUT
Degree Programme
Information Technology
Files
Status
defended, grade B
Date
12 June 2017
Reviewer
Hradiš Michal, Ing., Ph.D.
Committee
Herout Adam, prof. Ing., Ph.D. (DCGM FIT BUT), předseda
Češka Milan, doc. RNDr., Ph.D. (DITS FIT BUT), člen
Drábek Vladimír, doc. Ing., CSc. (DCSY FIT BUT), člen
Hliněná Dana, doc. RNDr., Ph.D. (DMAT FEEC BUT), člen
Rychlý Marek, RNDr., Ph.D. (DIFS FIT BUT), člen
Citation
TRÁVNÍČKOVÁ, Kateřina. Hluboké neuronové sítě pro analýzu medicínských obrazových dat. Brno, 2017. Bachelor's Thesis. Brno University of Technology, Faculty of Information Technology. 2017-06-12. Supervised by Španěl Michal. Available from: https://www.fit.vut.cz/study/thesis/19460/
BibTeX 
@bachelorsthesis{FITBT19460,
    author = "Kate\v{r}ina Tr\'{a}vn\'{i}\v{c}kov\'{a}",
    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 = 2017,
    location = "Brno, CZ",
    language = "czech",
    url = "https://www.fit.vut.cz/study/thesis/19460/"
}

Theses

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