Content-based medical image retrieval system for infections and fluids in chest radiographs

Siti Halimatul Munirah Wan Ahmad Wan Siti Halimatul Munirah Wan Ahmad, Wan Mimi Diyana Wan Zaki, Mohammad Faizal Ahmad Fauzi, Tan Wooi Haw

Research output: Contribution to journalArticle

Abstract

This paper presents a retrieval system based on the image’s content for the application in medical domain. This system is aimed to assist the radiologists in healthcare by providing pertinent supporting evidence from previous cases. It is also useful for the junior radiologists and medical students as teaching aid and training mechanism. The system is tested to retrieve the infections and fluid cases in chest radiographs. We explored several feature extraction techniques to see their effectiveness in describing the low-level property of the radiographs in our dataset. These features are Gabor transform, Discrete Wavelet Frame and Grey Level Histogram. The retrieval of these cases was also experimented with a number of distance metrics to observe their performances. Promising measures based on recognition rate are reported.

Original languageEnglish
Pages (from-to)14-23
Number of pages10
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8870
Publication statusPublished - 2014

Fingerprint

Discrete wavelet transforms
Image retrieval
Image Retrieval
Medical Image
Infection
Feature extraction
Teaching
Students
Fluid
Fluids
Retrieval
Gabor Transform
Wavelet Frames
Distance Metric
Healthcare
Histogram
Feature Extraction

Keywords

  • Chest x-ray
  • Content-based medical image retrieval
  • Discrete Wavelet Frame
  • Gabor transforms
  • Grey Level Histogram
  • Lung fluid
  • Lung infection

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Content-based medical image retrieval system for infections and fluids in chest radiographs. / Wan Siti Halimatul Munirah Wan Ahmad, Siti Halimatul Munirah Wan Ahmad; Wan Zaki, Wan Mimi Diyana; Faizal Ahmad Fauzi, Mohammad; Haw, Tan Wooi.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 8870, 2014, p. 14-23.

Research output: Contribution to journalArticle

@article{222d0a059e8944cd8966fbe991def085,
title = "Content-based medical image retrieval system for infections and fluids in chest radiographs",
abstract = "This paper presents a retrieval system based on the image’s content for the application in medical domain. This system is aimed to assist the radiologists in healthcare by providing pertinent supporting evidence from previous cases. It is also useful for the junior radiologists and medical students as teaching aid and training mechanism. The system is tested to retrieve the infections and fluid cases in chest radiographs. We explored several feature extraction techniques to see their effectiveness in describing the low-level property of the radiographs in our dataset. These features are Gabor transform, Discrete Wavelet Frame and Grey Level Histogram. The retrieval of these cases was also experimented with a number of distance metrics to observe their performances. Promising measures based on recognition rate are reported.",
keywords = "Chest x-ray, Content-based medical image retrieval, Discrete Wavelet Frame, Gabor transforms, Grey Level Histogram, Lung fluid, Lung infection",
author = "{Wan Siti Halimatul Munirah Wan Ahmad}, {Siti Halimatul Munirah Wan Ahmad} and {Wan Zaki}, {Wan Mimi Diyana} and {Faizal Ahmad Fauzi}, Mohammad and Haw, {Tan Wooi}",
year = "2014",
language = "English",
volume = "8870",
pages = "14--23",
journal = "Lecture Notes in Computer Science",
issn = "0302-9743",
publisher = "Springer Verlag",

}

TY - JOUR

T1 - Content-based medical image retrieval system for infections and fluids in chest radiographs

AU - Wan Siti Halimatul Munirah Wan Ahmad, Siti Halimatul Munirah Wan Ahmad

AU - Wan Zaki, Wan Mimi Diyana

AU - Faizal Ahmad Fauzi, Mohammad

AU - Haw, Tan Wooi

PY - 2014

Y1 - 2014

N2 - This paper presents a retrieval system based on the image’s content for the application in medical domain. This system is aimed to assist the radiologists in healthcare by providing pertinent supporting evidence from previous cases. It is also useful for the junior radiologists and medical students as teaching aid and training mechanism. The system is tested to retrieve the infections and fluid cases in chest radiographs. We explored several feature extraction techniques to see their effectiveness in describing the low-level property of the radiographs in our dataset. These features are Gabor transform, Discrete Wavelet Frame and Grey Level Histogram. The retrieval of these cases was also experimented with a number of distance metrics to observe their performances. Promising measures based on recognition rate are reported.

AB - This paper presents a retrieval system based on the image’s content for the application in medical domain. This system is aimed to assist the radiologists in healthcare by providing pertinent supporting evidence from previous cases. It is also useful for the junior radiologists and medical students as teaching aid and training mechanism. The system is tested to retrieve the infections and fluid cases in chest radiographs. We explored several feature extraction techniques to see their effectiveness in describing the low-level property of the radiographs in our dataset. These features are Gabor transform, Discrete Wavelet Frame and Grey Level Histogram. The retrieval of these cases was also experimented with a number of distance metrics to observe their performances. Promising measures based on recognition rate are reported.

KW - Chest x-ray

KW - Content-based medical image retrieval

KW - Discrete Wavelet Frame

KW - Gabor transforms

KW - Grey Level Histogram

KW - Lung fluid

KW - Lung infection

UR - http://www.scopus.com/inward/record.url?scp=84921650199&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84921650199&partnerID=8YFLogxK

M3 - Article

VL - 8870

SP - 14

EP - 23

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

ER -