A system for determination of 3D vessel tree centerlines from biplane images
 Kenneth R. Hoffmann,
 Anindya Sen,
 Li Lan,
 KokGee Chua,
 Jacqueline Esthappan,
 Marco Mazzucco
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With the increasing number and complexity of therapeutic coronary interventions, there is an increasing need for accurate quantitative measurements. These interventions and measurements may be facilitated by accurate and reproducible magnifications and orientations of the vessel structures, specifically by accurate 3D vascular tree centerlines. A number of methods have been proposed to calculate 3D vascular tree centerlines from biplane images. In general, the calculated magnifications and orientations are accurate to within approximately 1–3% and 2–5°, respectively. Here, we present a complete system for determination of the 3D vessel centerlines from biplane angiograms without the use of a calibration object. Subsequent to indication of the vessel centerlines, the imaging geometry and 3D centerlines are calculated automatically and within approximately 2 min. The system was evaluated in terms of the intra and interuser variations of the various calculated quantities. The reproducibilities obtained with this system are comparable to or better than the accuracies and reproducibilities quoted for other proposed methods. Based on these results and those reported in earlier studies, we believe that this system will provide accurate and reproducible vascular tree centerlines from biplane images while the patient is still on the table, and thereby will facilitate interventions and associated quantitative analyses of the vasculature.
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 Title
 A system for determination of 3D vessel tree centerlines from biplane images
 Journal

The International Journal of Cardiac Imaging
Volume 16, Issue 5 , pp 315330
 Cover Date
 20001001
 DOI
 10.1023/A:1026528209003
 Print ISSN
 01679899
 Online ISSN
 15730743
 Publisher
 Kluwer Academic Publishers
 Additional Links
 Topics
 Keywords

 biplane angiography
 threedimensional
 vascular analysis
 Industry Sectors
 Authors

 Kenneth R. Hoffmann ^{(1)}
 Anindya Sen ^{(2)}
 Li Lan ^{(3)}
 KokGee Chua ^{(4)}
 Jacqueline Esthappan ^{(3)}
 Marco Mazzucco ^{(5)}
 Author Affiliations

 1. Toshiba Stroke Research Center, Department of Neurosurgery, SUNY at Buffalo, Buffalo, NY, USA
 2. BioImaging Research, Chicago, IL, USA
 3. Kurt Rossmann Laboratories for Radiologic Image Research, Department of Radiology, The University of Chicago, Chicago, IL, USA
 4. Fox Valley Cardiovascular Consultants, Aurora, IL, USA
 5. Department of Mathematics, University of Illinois in Chicago, Chicago, IL, USA