Wavelet based rotation invariant texture feature for lung tissue classification and retrieval

Jatindra Kumar Dash; Sudipta Mukhopadhyay; Rahul Das Gupta; Mandeep Kumar Garg; Nidhi Prabhakar; Niranjan Khandelwal

doi:10.1117/12.2043157

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18 March 2014 Wavelet based rotation invariant texture feature for lung tissue classification and retrieval

Jatindra Kumar Dash, Sudipta Mukhopadhyay, Rahul Das Gupta, Mandeep Kumar Garg, Nidhi Prabhakar, Niranjan Khandelwal

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Proceedings Volume 9035, Medical Imaging 2014: Computer-Aided Diagnosis; 90352G (2014) https://doi.org/10.1117/12.2043157
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

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.

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Jatindra Kumar Dash, Sudipta Mukhopadhyay, Rahul Das Gupta, Mandeep Kumar Garg, Nidhi Prabhakar, and Niranjan Khandelwal "Wavelet based rotation invariant texture feature for lung tissue classification and retrieval", Proc. SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis, 90352G (18 March 2014); https://doi.org/10.1117/12.2043157

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