An Enhanced ILD Diagnosis Method using DWT

Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2013, Vol 13, Issue 1

Abstract

 Interstitial Lung Disease (ILD) is a group of lung diseases affecting lung parenchyma. Since the lesions can be clearly identified in the CT scan of the lung, CT analysis is best among the ways for the identification of ILD by the pathologists. The automated detection of any disease from images uses the same fact  that they are diagnosed by the medical professionals by exploiting the appearance features of the image of  organ under consideration. Here we are applying the same to detect Lung Diseases from CT images.  Segmenting the arteries and veins from the image is one of the major steps in analyzing the medical image. We  need an edge enhanced lung image to do the same, so that the vascular tree can be clearly identified. In this  implementation, discrete wavelet transform is applied for edge enhancement followed by the dynamic range  compression. Wavelet edge enhancement and vessel enhancement filtering comprises the first stage of the  algorithm. Vessel enhancement filtering uses the Eigen values of the Hessian of the image. The second stage of  the algorithm corresponds to the feature extraction and classification. Feature extraction is done from the cooccurrence matrix of the resulting vessel segmented image. The co-occurrence features of the image forms the  input feature vector for fuzzy SVM classifier. The performance of the proposed scheme is evaluated for accuracy.

Authors and Affiliations

Viji P. S

Keywords

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  • EP ID EP98729
  • DOI -
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How To Cite

Viji P. S (2013).  An Enhanced ILD Diagnosis Method using DWT. IOSR Journals (IOSR Journal of Computer Engineering), 13(1), 128-133. https://europub.co.uk/articles/-A-98729