IIUM Repository

Multi-level of feature extraction and classification for X-Ray medical image

Abdulrazaq, M and Alshaikhli, Imad Fakhri Taha and Mohd Noah, Shahrul Azman and Fadhil,, Moayad Al Athami (2018) Multi-level of feature extraction and classification for X-Ray medical image. Indonesian Journal of Electrical Engineering and Computer Science, 10 (1). pp. 154-167. ISSN 2502-4752

[img] PDF (SCOPUS) - Supplemental Material
Restricted to Registered users only

Download (518kB) | Request a copy
[img] PDF - Published Version
Restricted to Registered users only

Download (784kB) | Request a copy

Abstract

There has been a rise in demand for digitized medical images over the last two decades. Medical images' pivotal role in surgical planning is also an essential source of information for diseases and as medical reference as well as for the purpose of research and training. Therefore, effective techniques for medical image retrieval and classification are required to provide accurate search through substantial amount of images in a timely manner. Given the amount of images that are required to deal with, it is a non-viable practice to manually annotate these medical images. Additionally, retrieving and indexing them with image visual feature cannot capture high level of semantic concepts, which are necessary for accurate retrieval and effective classification of medical images. Therefore, an automatic mechanism is required to address these limitations. Addressing this, this study formulated an effective classification for X-ray medical images using different feature extractions and classification techniques. Specifically, this study proposed pertinent feature extraction algorithm for X-ray medical images and determined machine learning methods for automatic X-ray medical image classification. This study also evaluated different image features (chiefly global, local, and combined) and classifiers. Consequently, the obtained results from this study improved results obtained from previous related studies.

Item Type: Article (Journal)
Additional Information: 6534/63248
Uncontrolled Keywords: X-ray medical image, SVM, K-NN, Feature Extraction, Classification
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Information and Communication Technology > Department of Computer Science
Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User: Professor Imad Taha
Date Deposited: 16 Apr 2018 11:31
Last Modified: 10 Aug 2018 11:32
URI: http://irep.iium.edu.my/id/eprint/63248

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year