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|Title:||Registration of pre-operative CT and non-contrast-enhanced C-arm CT: An application to trans-catheter aortic valve implantation (TAVI)|
|Source:||Lu, Y.,Sun, Y.,Liao, R.,Ong, S.H. (2013). Registration of pre-operative CT and non-contrast-enhanced C-arm CT: An application to trans-catheter aortic valve implantation (TAVI). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7725 LNCS (PART 2) : 268-280. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-37444-9_21|
|Abstract:||Trans-catheter Aortic Valve Implantation (TAVI) has proven to be an effective minimal-invasive alternative to traditional open-heart valve replacement surgery. Despite the success of contrast enhanced C-arm CT for intra-operative guidance during TAVI, utilization of pre-operative CT in the Hybrid Operating Room provides additional advantages of an improved workflow and minimized usage of contrast agent. In this paper, we propose a framework for CT/non-contrast-enhanced C-arm CT volume registration so that pre-operative CT can be used intra-operatively without additional contrast medium. The proposed method consists of two steps, rigid-body coarse alignment followed by deformable fine registration. Our contribution is twofold. First, robust heart center detection on both image modalities is used to boost the success rate of rigid-body registration. Second, a structural encoded similarity measure and anatomical correlation-regularized deformation fields are proposed to improve the performance of intensity-based deformable registration using the variational framework. Experiments were performed on ten sets of TAVI patient data, and the results have shown that the proposed method provides a highly robust and accurate registration. The resulting accuracy of 1.83 mm mean mesh-to-mesh error at the aortic root and the high efficiency of an average running time of 2 minutes on a common computer make it potentially feasible for clinical usage in TAVI. The proposed heart registration method is generic and hence can be easily applied to other cardiac applications. © 2013 Springer-Verlag.|
|Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Appears in Collections:||Staff Publications|
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