RATIONALE AND OBJECTIVES: Two-dimensional and three-dimensional (2D-3D) registration for angiographic liver interventions is an unsolved problem mainly because of two reasons. First, a suitable protocol for computed tomography angiography (CTA) to contrast liver arteries is not used in clinical practice. Second, in spite of a valuable body of research results in the neuroradiology community, an adequate registration algorithm that addresses the difficult task of 2D-3D alignment of abdominal vessel structures has not been developed yet. MATERIALS AND METHODS: We address the first issue by introducing an angiographic computed tomography (CT) scanning phase. The scan visualizes arteries similar to the vasculature captured with an intraoperative C-arm acquiring digitally subtracted angiograms. Furthermore, we propose a registration algorithm using the new CT phase that aligns arterial structures in two steps: 1) Initialization of one corresponding feature using diameter information and 2) optimization on three rotational and one translational parameters to register vessel structures that are represented as centerline graphs. We form a space of good features by iteratively creating new graphs from projected centerline images and by restricting the correspondence search only on branching points (the vertices) of the vessel tree. RESULTS: We show convergence and robustness of the proposed algorithm on synthetic data, as well as head phantom and four consistent patient data sets. We compare our results with those of a recently proposed method. Moreover, we evaluate different visualization techniques and show that a transfer of planning information to intraoperative data is a benefit for interventional workflow. CONCLUSIONS: Introducing a new CTA protocol and a two-step 2D-3D registration algorithm, the proposed method creates a strong link between radiologists and interventionalists by bringing preoperative patient and planning information to interventional workflow.
RATIONALE AND OBJECTIVES: Two-dimensional and three-dimensional (2D-3D) registration for angiographic liver interventions is an unsolved problem mainly because of two reasons. First, a suitable protocol for computed tomography angiography (CTA) to contrast liver arteries is not used in clinical practice. Second, in spite of a valuable body of research results in the neuroradiology community, an adequate registration algorithm that addresses the difficult task of 2D-3D alignment of abdominal vessel structures has not been developed yet. MATERIALS AND METHODS: We address the first issue by introducing an angiographic computed tomography (CT) scanning phase. The scan visualizes arteries similar to the vasculature captured with an intraoperative C-arm acquiring digitally subtracted angiograms. Furthermore, we propose a registration algorithm using the new CT phase that aligns arterial structures in two steps: 1) Initialization of one corresponding feature using diameter information and 2) optimization on three rotational and one translational parameters to register vessel structures that are represented as centerline graphs. We form a space of good features by iteratively creating new graphs from projected centerline images and by restricting the correspondence search only on branching points (the vertices) of the vessel tree. RESULTS: We show convergence and robustness of the proposed algorithm on synthetic data, as well as head phantom and four consistent patient data sets. We compare our results with those of a recently proposed method. Moreover, we evaluate different visualization techniques and show that a transfer of planning information to intraoperative data is a benefit for interventional workflow. CONCLUSIONS: Introducing a new CTA protocol and a two-step 2D-3D registration algorithm, the proposed method creates a strong link between radiologists and interventionalists by bringing preoperative patient and planning information to interventional workflow.
Authors: Christelle Gendrin; Primoz Markelj; Supriyanto Ardjo Pawiro; Jakob Spoerk; Christoph Bloch; Christoph Weber; Michael Figl; Helmar Bergmann; Wolfgang Birkfellner; Bostjan Likar; Franjo Pernus Journal: Med Phys Date: 2011-03 Impact factor: 4.071
Authors: Ada Muellner; Gary M Glazer; Maximilian F Reiser; William G Bradley; Gabriel P Krestin; Hedvig Hricak; James H Thrall Journal: Eur Radiol Date: 2009-03-11 Impact factor: 5.315