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Lung segmentation on standard and mobile chest radiographs using oriented Gaussian derivatives filter

Wan Ahmad WS 1 , Zaki WM 2 , Ahmad Fauzi MF 3

Affiliations 

  • 1 Faculty of Engineering, Multimedia University, Persiaran Multimedia, Cyberjaya, Selangor, Malaysia. wshmunirah@gmail.com
  • 2 Department of Electric, Electronic & Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia. wmdiyana@eng.ukm.my
  • 3 Faculty of Engineering, Multimedia University, Persiaran Multimedia, Cyberjaya, Selangor, Malaysia. faizal1@mmu.edu.my
Biomed Eng Online, 2015;14:20.
PMID: 25889188 DOI: 10.1186/s12938-015-0014-8

Abstract

Unsupervised lung segmentation method is one of the mandatory processes in order to develop a Content Based Medical Image Retrieval System (CBMIRS) of CXR. The purpose of the study is to present a robust solution for lung segmentation of standard and mobile chest radiographs using fully automated unsupervised method.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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