This paper evaluates the performance of recently proposed rotation invariant texture feature extraction method for the classīcation 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 classīcation accuracy. © 2014 SPIE.