Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/19014
Title: Classification of magnetic resonance images
Authors: Trojachanec, Katarina 
Madzarov, Gjorgji
Gjorgjevikj, Dejan
Loshkovska, Suzana
Keywords: Classification, Support Vector Machines (SVMs), Magnetic Resonance Images (MRIs), neural networks
Issue Date: 21-Jun-2010
Publisher: IEEE
Conference: Proceedings of the ITI 2010, 32nd International Conference on Information Technology Interfaces
Abstract: The aim of the paper is to compare classification error of the classifiers applied to magnetic resonance images for each descriptor used for feature extraction. We compared several Support Vector Machine (SVM) techniques, neural networks and k nearest neighbor classifier for classification of Magnetic Resonance Images (MRIs). Different descriptors are applied to provide feature extraction from the images. The dataset used for classification contains magnetic resonance images classified in 9 classes.
URI: http://hdl.handle.net/20.500.12188/19014
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers

Files in This Item:
File Description SizeFormat 
10.1.1.404.744.pdf126.29 kBAdobe PDFView/Open
Show full item record

Page view(s)

43
checked on May 20, 2024

Download(s)

5
checked on May 20, 2024

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.