Ventricular shape visualization using selective volume rendering of cardiac datasets

In this paper, we present a novel technique of improving volume rendering q uality and speed by integrating original volume data and global model infor mation attained by segmentation. The segmentation information prevents obje ct occlusions that may appear when volume rendering is based on local image features only. Thus the presented visualization technique provides meaning ful visual results that enable a clear understanding of complex anatomical structures. In the first part, we describe a segmentation technique for ext racting the region of interest based on an active contour model. In the sec ond part, we propose a volume rendering method for visualizing the selected portions of fuzzy surfaces extracted by local image processing methods. We show the results of selective volume rendering of left and right ventricle based on cardiac datasets from clinical routines. Our method offers an acc elerated technique to accurately visualize the surfaces of segmented object s. (C) 2001 Elsevier Science Ltd. All rights reserved.