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We propose an automatic four-chamber heart segmentation system for the quantitative functional analysis of the heart from cardiac computed tomography (CT) volumes. Two topics are discussed: heart modeling and automatic model fitting to an unseen volume. Heart modeling is a nontrivial task since the heart is a complex nonrigid organ. The model must be(More)
Minimally invasive liver interventions demand a lot of experience due to the limited access to the field of operation. In particular, the correct placement of the trocar and the navigation within the patient's body are hampered. In this work, we present an intraoperative augmented reality system (IARS) that directly projects preoperatively planned(More)
OBJECTIVE To analyze the diagnostic efficacy of computer aided analysis of relevant coronary artery stenosis using dual source computed tomography (DSCT). METHODS In a larger scale study patients scheduled for conventional coronary angiography (CA) were additionally examined with DSCT. Based on a 13-segment model 30 CT scans of this study population were(More)
OBJECTIVES To evaluate the performance of three-dimensional semi-automated evaluation software for the assessment of myocardial blood flow (MBF) and blood volume (MBV) at dynamic myocardial perfusion computed tomography (CT). METHODS Volume-based software relying on marginal space learning and probabilistic boosting tree-based contour fitting was applied(More)
Multi-chamber heart segmentation is a prerequisite for global quantification of the cardiac function. The complexity of cardiac anatomy, poor contrast, noise or motion artifacts makes this segmentation problem a challenging task. In this paper, we present an efficient, robust, and fully automatic segmentation method for 3D cardiac computed tomography (CT)(More)
High performance deformation of volumetric objects is a common problem in computer graphics that has not yet been handled sufficiently. As a supplement to 3D texture based volume rendering, a novel approach is presented, which adaptively subdivides the volume into piecewise linear patches. An appropriate mathematical model based on tri-linear interpolation(More)
Recently, we proposed marginal space learning (MSL) as a generic approach for automatic detection of 3D anatomical structures in many medical imaging modalities. To accurately localize a 3D object, we need to estimate nine parameters (three for position, three for orientation, and three for anisotropic scaling). Instead of uniformly searching the original(More)
OBJECTIVES The aim of this study was to quantify image quality gains of a moving coronary plaque phantom using dual-source computed tomography (DSCT) providing 83 milliseconds temporal resolution in direct comparison to 64 slice single-source multidetector CT (MDCT) with a temporal resolution of 165 milliseconds. MATERIALS AND METHODS Three cardiac vessel(More)