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Abstract #3823

Hough-transform based detection of vascular structures applied to automate and accelerate planning of super-selective Arterial Spin Labeling

Thomas Lindner1, Olav Jansen1, and Michael Helle2

1Clinic for Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Kiel, Germany, 2Tomographic Imaging Department, Philips Research, Hamburg, Germany

Super-selective Arterial Spin Labeling (ASL) is a technique to perform non-contrast enhanced flow territory mapping. Prior to image acquisition, the labeling focus has to be positioned on each artery of interest separately. Depending on the arterial architecture, this process can be time-consuming, especially for untrained operators. In this study, an algorithm for automated vessel detection and planning is introduced to accelerate the planning procedure of super-selective ASL measurements, which is based on the Hough transform to detect circular structures (i.e. arteries) on a transversal time-of-flight (TOF) scan.

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