Automatic vessel segmentation using active contours in cine phase contrastflow measurements

The segmentation of images obtained by cine magnetic resonance (MR) phase c ontrast velocity mapping using manual or semi-automated methods is a time c onsuming and observer-dependent process that still hampers the use of now q uantification in a clinical setting. A fully automatic segmentation method based on active contour model algorithms for defining vessel boundaries has been developed, For segmentation, the phase image, in addition to the magn itude image, is used to address image distortions frequently seen in the ma gnitude image of disturbed now fields. A modified definition for the active contour model is introduced to reduce the influence of missing or spurious edge information of the vessel wall. The method was evaluated on now phant om data and on in vivo images acquired in the ascending aorta of humans. Ph antom experiments resulted in an error of 0.8% in assessing the luminal are a of a now phantom equipped with an artificial heart valve. Blinded evaluat ion of the volume now rates from automatic vs. manual segmentation of gradi ent echo (FFE) phase contrast images obtained in vivo resulted in a mean di fference of -0.9 +/- 3%. The mean difference from automatic vs. manual segm entation of images acquired with a hybrid phase contrast sequence (TFEPI) w ithin a single breath-hold was -0.9 +/- 6%. J. Magn. Reson. Imaging 1999: 1 0:41-51. (C) 1999 Wiley-Liss, Inc.