Ola Friman1, Anja Hennemuth1, Andreas Harloff2, Jelena Bock3, Michael Markl3, Heinz-Otto Peitgen1
1Fraunhofer MEVIS, Bremen, Germany; 2Neurology and Clinical Neurophysiology, Albert-Ludwigs Universitt, Freiburg, Germany; 3Diagnostic Radiology, Medical Physics, Albert-Ludwigs Universitt, Freiburg, Germany
Standard techniques for visualizing and quantifying flow data obtained with phase contrast (PC) MRI treat the measurements as if they were free of noise. This practice may lend the results a false sense of precision. This work contributes a flow connectivity mapping algorithm that models the noise in PC MRI velocity measurements and visualizes the flow uncertainty as a probabilistic flow distribution. New probabilistic measures such as the assignment of likelihoods to flow pathways to evaluate mixing of blood, or to quantify embolization probabilities in stroke and infarction, are also envisaged.