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Direct estimation of cardiac ventricular volumes has become increasingly popular and important in cardiac function analysis due to its effectiveness and efficiency by avoiding an intermediate segmentation step. However, existing methods rely on either intensive user inputs or problematic assumptions. To realize the full capacities of direct estimation, this(More)
We developed a quantitative Dynamic Contrast-Enhanced CT (DCE-CT) technique for measuring Myocardial Perfusion Reserve (MPR) and Volume Reserve (MVR) and studied their relationship with coronary stenosis. Twenty-six patients with Coronary Artery Disease (CAD) were recruited. Degree of stenosis in each coronary artery was classified from catheter-based(More)
BACKGROUND Transmural scar occupying left ventricular (LV) pacing regions has been associated with reduced response to cardiac resynchronization therapy (CRT). However, spatial influences of lead tip delivery relative to scar at both pacing sites remain poorly explored. This study evaluated scar distribution relative to LV and right ventricular (RV) lead(More)
Accurate estimation of the ventricular volumes is essential to the assessment of global cardiac functions. The existing estimation methods are mostly restricted to the left ventricle (LV), and often require segmentation which is challenging and computationally expensive. This paper proposes to estimate the volumes of both LV and right ventricle (RV) jointly(More)
Accurate estimation of ventricular volumes plays an essential role in clinical diagnosis of cardiac diseases. Existing methods either rely on segmentation or are restricted to direct estimation of the left ventricle. In this paper, we propose a novel method for direct and joint volume estimation of bi-ventricles, i.e., the left and right ventricles, without(More)
Automating the detection and localization of segmental (regional) left ventricle (LV) abnormalities in magnetic resonance imaging (MRI) has recently sparked an impressive research effort, with promising performances and a breadth of techniques. However, despite such an effort, the problem is still acknowledged to be challenging, with much room for(More)
This study investigates regional heart motion abnormality detection using various classifier features with Shannon's Differential Entropy (SDE). Rather than relying on elementary measurements or a fixed set of moments, the SDE measures global distribution information and, as such, has more discriminative power in classifying distributions. Based on(More)
We present a discrete kernel density matching energy for segmenting the left ventricle cavity in cardiac magnetic resonance sequences. The energy and its graph cut optimization based on an original first-order approximation of the Bhattacharyya measure have not been proposed previously, and yield competitive results in nearly real-time. The algorithm seeks(More)
We present an original information theoretic measure of heart motion based on the Shannon's differential entropy (SDE), which allows heart wall motion abnormality detection. Based on functional images, which are subject to noise and segmentation inaccuracies, heart wall motion analysis is acknowledged as a difficult problem, and as such, incorporation of(More)