Extraction of myocardial wall from cardiac CT images

Congenital heart diseases like Atrial Septal Defect, Ventricular Septal Defect and plaque can be found by delineation of myocardial wall. Cardiac Computed Tomography is a non invasive imaging technique used for diagnosis of coronary artery diseases. Cardiac chamber segmentation is particularly valuable for the extraction of myocardial wall, because changes in the thickness of myocardium are used to detect the abnormality in heart functions. In this paper initially image is pre-processed using median filter and edge detection operator. The Left Ventricle and Right Ventricle are segmented using two algorithms, Region Growing and Active Contour Model. Moving window concept is introduced for seed selection and mask initialization. Relevant Gray Level Co-occurrence Matrix features are extracted for classification purpose. Finally the segmented image is classified using Adaptive Neural Fuzzy Inference System classifier.