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Refinement and expansion of matched vessel graphs for intraoperative deformable registration of hepatic CT and ultrasound

 
: Keil, Matthias; Kaisler, Alexander; Oyarzun Laura, Cristina; Wesarg, Stefan

:

Holmes, D.R. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Medical imaging 2013. Image-guided procedures, robotic interventions, and modeling : 12 - 14 February 2013, Lake Buena Vista, Florida, United States
Bellingham, WA: SPIE, 2013 (Proceedings of SPIE 8671)
ISBN: 978-0-8194-9445-0
Paper 867107
Image-Guided Procedures, Robotic Interventions, and Modeling Conference <2013, Lake Buena Vista/Fla.>
English
Conference Paper
Fraunhofer IGD ()
vessel segmentation; ultrasound; computed tomography (CT); graphs; refinement; registration; image guided therapy

Abstract
Multimodal registration of intraoperative ultrasound and preoperative contrast enhanced computed tomography (CT) imaging is the basis for image guided percutaneous hepatic interventions. Currently, the surgeon manually performs a rigid registration using vessel structures and other anatomical landmarks for visual guidance. We have previously presented our approach for an automation of this intraoperative registration step based on the definition of bijective correspondences between the vessel structures using an automatic graph matching.1 This paper describes our method for refinement and expansion of the matched vessel graphs, resulting in a high number of bijective correspondences. Based on these landmarks, we could extend our method to a fully deformable registration. Our system was applied successfully on CT and ultrasound data of nine patients, which are studied in this paper. The number of corresponding vessel points could be raised from a mean of 9.6 points after the graph matching to 70.2 points using the presented refinement method. This allows for the computation of a smooth deformation field. Furthermore, we can show that our deformation calculation raises the registration accuracy for 3 of the 4 chosen target vessels in pre-/postoperative CT with a mean accuracy improvement of 44%.

: http://publica.fraunhofer.de/documents/N-264630.html