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Proceedings Paper

Wavelet based rotation invariant texture feature for lung tissue classification and retrieval
Author(s): Jatindra Kumar Dash; Sudipta Mukhopadhyay; Rahul Das Gupta; Mandeep Kumar Garg; Nidhi Prabhakar; Niranjan Khandelwal
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Paper Abstract

This paper evaluates the performance of recently proposed rotation invariant texture feature extraction method for the classi¯cation and retrieval of lung tissues a®ected with Interstitial Lung Diseases (ILDs). The method makes use of principle texture direction as the reference direction and extracts texture features using Discrete Wavelet Transform (DWT). A private database containing high resolution computed tomography (HRCT) images belonging to ¯ve category of lung tissue is used for the experiment. The experimental result shows that the texture appearances of lung tissues are anisotropic in nature and hence rotation invariant features achieve better retrieval as well as classi¯cation accuracy.

Paper Details

Date Published: 18 March 2014
PDF: 6 pages
Proc. SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis, 90352G (18 March 2014); doi: 10.1117/12.2043157
Show Author Affiliations
Jatindra Kumar Dash, Indian Institute of Technology Kharagpur (India)
Sudipta Mukhopadhyay, Indian Institute of Technology Kharagpur (India)
Rahul Das Gupta, Indian Institute of Technology Kharagpur (India)
Mandeep Kumar Garg, Postgraduate Institute of Medical Education & Research (India)
Nidhi Prabhakar, Postgraduate Institute of Medical Education & Research (India)
Niranjan Khandelwal, Postgraduate Institute of Medical Education & Research (India)


Published in SPIE Proceedings Vol. 9035:
Medical Imaging 2014: Computer-Aided Diagnosis
Stephen Aylward; Lubomir M. Hadjiiski, Editor(s)

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