Domain Analysis Of Common Carotid Artery Images Using Multiwavelets For The Diagnosis Of Cardiovascular Diseases

1322 WordsOct 23, 20146 Pages
1 Transform Domain Analysis of Common Carotid Artery Images using Multiwavelets for the Diagnosis of Cardiovascular Diseases R.Nandakumar 1 and K.B. Jayanthi 2 1Professor, Department of ECE, K.S.R.Institute for Engineering and Technology 2Professor, Department of ECE, K.S.Rangasamy College of Technology E-mail: nandhu.r79@gmail.com, jayanthikb@gmail.com ABSTRACT: According to the report given by World Health Organization, by 2015 almost 20 million people will die from cardiovascular diseases (CVD). People in low- and middle-income countries who suffer from CVDs and other noncommunicable diseases have less access to effective and equitable health care services which respond to their needs. The main objective of this work is to develop a classifier for the diagnosis of abnormal Common Carotid Arteries (CCA). This paper proposes a new approach for the transform domain analysis of longitudinal B-mode ultrasound CCA images using Multiwavelets. Analysis is done using HM and GHM multiwavelets at various levels of decomposition. Multiwavelet preserves high frequency information in image and provides good energy compaction efficiency. Energy values of the coefficients of approximation, horizontal, vertical and diagonal details are calculated and plotted for different levels. Plots of energy values show high correlation with the abnormalities of CCA and offer the possibility of improved diagnosis of CVD. It is clear that the energy values can be used as an index of individual

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