title: Model-based segmentation and motion analysis of the thoracic aorta from 4D ECG-gated CTA images.
abstract: Pathologies of the thoracic aorta can alter the shape and motion pattern of the aorta throughout the cardiac cycle. For diagnosis and therapy planning, determination of the aortic shape and motion is important. We introduce a new approach for segmentation and motion analysis of the thoracic aorta from 4D ECG-CTA images, which combines spatial and temporal tracking, motion determination by intensity-based matching, and 3D fitting of vessel models. The approach has been successfully applied to 30 clinically relevant 4D CTA image sequences. We have also performed a quantitative evaluation of the segmentation accuracy.
authors: University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group.
authors: Andreas
authors: A
authors: Biesdorf
authors: Stefan
authors: S
authors: Wörz
authors: Tobias
authors: T
authors: Müller
authors: Tim Frederik
authors: TF
authors: Weber
authors: Tobias
authors: T
authors: Heye
authors: Waldemar
authors: W
authors: Hosch
authors: Hendrik
authors: H
authors: von Tengg-Kobligk
authors: Karl
authors: K
authors: Rohr
mesh_terms: D000465:Algorithms; D000792:Angiography / Q000379:methods*; D001011:Aorta / Q000473:pathology; D001013:Aorta, Thoracic / Q000000981:diagnostic imaging* / Q000473:pathology*; D003198:Computer Simulation; D004562:Electrocardiography / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D015233:Models, Statistical; D009038:Motion; D015203:Reproducibility of Results; D012984:Software; D013997:Time Factors; D014463:Ultrasonography