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By Hill F.S.

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9. Hering J, Gergel I, Kr¨ omker S, et al. MITK-OpenCL: Eine Erweiterung f¨ ur das Medical Imaging Interaction Toolkit. Proc BVM. 2011; p. 454–8. Glomerular Filtration Rate Estimation from Dynamic Contrast-Enhanced MRI Anna K. de Abstract. The treatment of chronic renal diseases usually involves the estimation of the glomerular filtration rate (GFR). The GFR can be estimated in vivo without blood samples by pharmacokinetic methods. These models employ non-linear curve fitting techniques to obtain model parameters fitting the model to concentration curves extracted from 4D DCE-MRI data.

Cortex and medulla, was segmented [1]. Moreover, the original MRI intensities were converted to the gadolinium concentration. This concentration was then averaged separately over each kidney and each time point, resulting in an estimate of CK for the each kidney at every time point. Finally, CA was estimated analogously using a manual segmentation of the aorta. In total, we use four datasets of this type, denoted by D1 to D4 , each with data for the left and the right kidney, for the evaluation.

B) Intuitive direkte Visualisierung an einem Puppenkopf mit Tumor (rot). 28 Heim et al. GPGPU A-ICP aus, um nah an die optimale L¨ osung zu kommen. Der HardwareAufbau besteht aus einer Tiefenbildkamera, die an einem Tablet-PC befestigt wird und einem Server. Die Kamera akquiriert Tiefendaten, welche auf dem Server mittels des GPGPU A-ICP mit medizinischen Daten registriert werden. Das Ergebnis der Registrierung erm¨ oglicht einen Blick ins Innere des Patienten mittels eines mobilen Displays (Abb.

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