slugEmphysema Detection usingRegion Growing based Active Contour ModelSegmentation

Abstract

Emphysema has large prevalence rate and remain as a healthcare challenge worldwide . Computer Aided Diagnosis (CAD) has become a major research interest in diagnostic radiology and medical imaging diagnostics. The basic goal of CAD is to provide a computer output as a second opinion to assist the technicians by reducingimage interpretation timeand improving diagnostic accuracy. In this work region growing based active contour segmentation technique is attempted for e xtracting the lung parenchyma in the CT lung images in order to detect emphysema . The active contour method provide s an effective way for segmentation, in which the boundaries of the objects are detected by evolving curves. In this work region growing output image is used as the mask for the active contour model and then texture features are extracted and the extracted features are classified using Extreme learning Machine classifier. Result shows that the automated method can detect emphysema efficiently.

Authors and Affiliations

R. Ambiga, C. M. Sujatha

Keywords

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  • EP ID EP18007
  • DOI -
  • Views 408
  • Downloads 18

How To Cite

R. Ambiga, C. M. Sujatha (2014). slugEmphysema Detection usingRegion Growing based Active Contour ModelSegmentation. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2(5), -. https://europub.co.uk/articles/-A-18007