caa a22 4500 605541450 CHVBK 20210128100916.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s00371-014-1024-4 doi (NATIONALLICENCE)springer-10.1007/s00371-014-1024-4 A parallelized 4D reconstruction algorithm for vascular structures and motions based on energy optimization [Elektronische Daten] [Xinglong Liu, Fei Hou, Aimin Hao, Hong Qin] In this paper, we present a parallel 4D vessel reconstruction algorithm that simultaneously recovers 3D structure, shape, and motion based on multiple views of X-ray angiograms. The fundamental goal is to assist the analysis and diagnosis of interventional surgery in the most efficient way towards interactive and accurate performance. We start with a fully parallelized algorithm to extract vessels as well as their skeletons and topologies from dynamic image sequences. Then, instead of resorting to registration, we present an algorithm to formulate the reconstruction problem as an energy minimization problem with color, coherence, and topology constraints to reconstruct the 3D vessel initially, which is robust to combat noise and incomplete information in images. Next, we incorporate temporal information into our energy optimization framework to track and reconstruct 4D kinematics of the dynamic vessels, which is also capable of recovering previous incomplete and misleading shapes acquired from static images otherwise. We demonstrate our system in coronary arteries reconstruction and movement tracking for percutaneous coronary intervention surgery to help medical practitioners learn about the 3D shapes and their motions of the coronary arteries of specific patient. We envision that our system would be of high assistance for diagnosis and therapy to treat vessel-related diseases in a clinical setting in the near future. Springer-Verlag Berlin Heidelberg, 2014 X-ray angiograms nationallicence 3D reconstruction nationallicence Motion tracking nationallicence Belief propagation nationallicence Liu Xinglong State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China aut Hou Fei State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China aut Hao Aimin State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China aut Qin Hong Department of Computer Science, Stony Brook University, Stony Brook, USA aut The Visual Computer Springer Berlin Heidelberg 31/11(2015-11-01), 1431-1446 0178-2789 31:11<1431 2015 31 371 https://doi.org/10.1007/s00371-014-1024-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00371-014-1024-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Liu Xinglong State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China aut NATIONALLICENCE 700 1- Hou Fei State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China aut NATIONALLICENCE 700 1- Hao Aimin State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China aut NATIONALLICENCE 700 1- Qin Hong Department of Computer Science, Stony Brook University, Stony Brook, USA aut NATIONALLICENCE 773 0- The Visual Computer Springer Berlin Heidelberg 31/11(2015-11-01), 1431-1446 0178-2789 31:11<1431 2015 31 371