Martin Schwartz1,2, Günter Steidle1, Petros Martirosian1, Bin Yang2, and Fritz Schick1
1Section on Experimental Radiology, Department of Radiology, University of Tuebingen, Tuebingen, Germany, 2Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany
The
segmentation of signal voids, which occur in time-series of single-shot
diffusion-weighted images, is important for an accelerated evaluation providing
larger studies on this phenomenon. The proposed segmentation is based on a
two-stage detection and segmentation approach, which utilizes a graph-based
representation with random walker optimization. It was demonstrated that the
presented method enables a fast and accurate segmentation of signal voids in
time-series of diffusion-weighted images.
