Original title: Convolutional Neural Networks For Identification Of Axial 2d Slices In Ct Data
Authors: Vavřinová, Pavlína
Document type: Papers
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: This thesis deals with the classification of 2D axial slices in CT patient’s data. The classification is realized into six categories. The sphere of convolutional neural networks was used for this purpose and AlexNet network was specifically selected for the intention of this identification, which was applied to the created data set after being adaptated. The overall classification success rate was 84%. In addition, an analysis of mistakes in classification was performed.
Keywords: AlexNet; convolutional neural networks; deep learning; neural networks
Host item entry: Proceedings of the 24th Conference STUDENT EEICT 2018, ISBN 978-80-214-5614-3

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/11012/138156

Permalink: http://www.nusl.cz/ntk/nusl-393342


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Universities and colleges > Public universities > Brno University of Technology
Conference materials > Papers