Detection of Lung Boundary in Chest X-rays using Adaptive Lung Atlas and Graph Cuts

Authors

  • Jeevitha Sivasamy  Ph.D., Scholar, Dept.of Computer and Information Science, Annamalai University, Annamalai Nagar,Tamilnadu, India.
  • Dr. T. S. Subashini   Associate Professor, Department of Computer Science & Engg., Annamalai University, Annamalai Nagar, Tamilnadu, India

Keywords:

CAD, Content Based Image Retrieval, Image Registration, Radon Transform, SIFT-Flow, Graph cut segmentation.

Abstract

In contrast to film X-rays the advent of digital X-rays has led to the use of computer assisted systems to automatically detect and diagnose diseases. Though CT and MRI are known for its diagnostic superiority Chest X-rays still remains the mainstay of chest imaging and is widely used by doctors to access various chest related ailments which includes pathologies related to lungs, esophagus, blood vessel, diaphragm, trachea, bronchia etc. The applicability of any computer aided diagnosis system (CAD) mainly depends on the accurate segmentation of the region of interest (ROI). In this work we have attempted to accurately segment the lung boundary using atlas based methods and non-rigid registration of atlases to patient specific adaptive lung models. The proposed work first applies a content based retrieval approach to select similar X-rays (lung masks) to that of the test X-ray using similarity measures and then an atlas of the test lung is obtained by SIFT-flow registration of the test X-ray with that of the retrieved masks. Finally graph-cut optimization is applied to extract the exact lung boundary.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-06-30

Issue

Volume 3, Issue 5, May-June-2018

Section

Research Articles

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How to Cite

[1]
Jeevitha Sivasamy, Dr. T. S. Subashini , " Detection of Lung Boundary in Chest X-rays using Adaptive Lung Atlas and Graph Cuts, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 5, pp.179-185, May-June-2018.