Suhaini B. Kadiman

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Medical image processing is nowadays one of the best tools to make an informative model from a raw image of each part of the body, and segmentation is the most important step in which used to extract significant features. Coronary artery segmentation algorithm in angiograms is a fundamental component of each cardiac image processing system. There are lots(More)
Segmentation is an important step in medical imaging to acquire qualitative measurements such as the location of the desired objects and also for quantitative measurements such as area, volume or the analysis of dynamic behaviour of anatomical structures over time. Among these images, ultrasound images play a crucial role, because they can be produced on(More)
Echocardiography imaging is one of the most widely used diagnostic tests for cardiovascular diseases which allow direct visualization of cardiac structure and ventricles wall motion. It can provide useful information, including the size and shape of the heart. An accurate method for border detection of ventricle wall motion is still important clinical(More)
This research aims to develop three dimensional geometrical tricuspid valve model using transesophagel echocardiography raw images (3DTEE). Main motivation that derives this research is the needs of volumetric image segmentation for surgical planning, post-surgical assessment, abnormality detection, and many other medical application. The challenge stands(More)
This paper presents a hybrid method to extract endocardial contour of the right ventricular (RV) in 4-slices from 3D echocardiography dataset. The overall framework comprises four processing phases. In Phase I, the region of interest (ROI) is identified by estimating the cavity boundary. Speckle noise reduction and contrast enhancement were implemented in(More)
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