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

Mohammed Muayad Abdulrazzaq, Imad Fakhri Taha Yaseen, Shahrul Azman Mohd Noah, Moayad Al Athami Fadhil

Research output: Contribution to journalArticle

3 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)154-167
Number of pages14
JournalIndonesian Journal of Electrical Engineering and Computer Science
Volume10
Issue number1
DOIs
Publication statusPublished - 1 Apr 2018

Fingerprint

Medical Image
Feature Extraction
Feature extraction
Image classification
X rays
Image retrieval
Learning systems
Image Classification
Classifiers
Semantics
Planning
Image Retrieval
Indexing
Machine Learning
Retrieval
Classifier
Necessary

Keywords

  • Classification
  • Feature extraction
  • K-NN
  • SVM
  • X-ray medical image

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications
  • Control and Optimization
  • Electrical and Electronic Engineering

Cite this

Multi-level of feature extraction and classification for X-ray medical image. / Abdulrazzaq, Mohammed Muayad; Yaseen, Imad Fakhri Taha; Mohd Noah, Shahrul Azman; Fadhil, Moayad Al Athami.

In: Indonesian Journal of Electrical Engineering and Computer Science, Vol. 10, No. 1, 01.04.2018, p. 154-167.

Research output: Contribution to journalArticle

Abdulrazzaq, Mohammed Muayad ; Yaseen, Imad Fakhri Taha ; Mohd Noah, Shahrul Azman ; Fadhil, Moayad Al Athami. / Multi-level of feature extraction and classification for X-ray medical image. In: Indonesian Journal of Electrical Engineering and Computer Science. 2018 ; Vol. 10, No. 1. pp. 154-167.
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