title: Locally adaptive 2D-3D registration using vascular structure model for liver catheterization.
abstract: Two-dimensional-three-dimensional (2D-3D) registration between intra-operative 2D digital subtraction angiography (DSA) and pre-operative 3D computed tomography angiography (CTA) can be used for roadmapping purposes. However, through the projection of 3D vessels, incorrect intersections and overlaps between vessels are produced because of the complex vascular structure, which makes it difficult to obtain the correct solution of 2D-3D registration. To overcome these problems, we propose a registration method that selects a suitable part of a 3D vascular structure for a given DSA image and finds the optimized solution to the partial 3D structure. The proposed algorithm can reduce the registration errors because it restricts the range of the 3D vascular structure for the registration by using only the relevant 3D vessels with the given DSA. To search for the appropriate 3D partial structure, we first construct a tree model of the 3D vascular structure and divide it into several subtrees in accordance with the connectivity. Then, the best matched subtree with the given DSA image is selected using the results from the coarse registration between each subtree and the vessels in the DSA image. Finally, a fine registration is conducted to minimize the difference between the selected subtree and the vessels of the DSA image. In experimental results obtained using 10 clinical datasets, the average distance errors in the case of the proposed method were 2.34±1.94mm. The proposed algorithm converges faster and produces more correct results than the conventional method in evaluations on patient datasets.
authors.affiliation: School of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-742, Korea. Electronic address: jhkim@cglab.snu.ac.kr.
authors.forename: Jihye
authors.initials: J
authors.lastname: Kim
authors.affiliation: School of Computer Science and Engineering, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 156-743, Korea. Electronic address: leejeongjin@ssu.ac.kr.
authors.forename: Jeongjin
authors.initials: J
authors.lastname: Lee
authors.affiliation: Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 110-744, Korea. Electronic address: chungjw@snu.ac.kr.
authors.forename: Jin Wook
authors.initials: JW
authors.lastname: Chung
authors.affiliation: School of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-742, Korea. Electronic address: yshin@snu.ac.kr.
authors.forename: Yeong-Gil
authors.initials: YG
authors.lastname: Shin
mesh_terms: D000792:Angiography; D002404:Catheterization; D006801:Humans; D021621:Imaging, Three-Dimensional; D008099:Liver / Q000098:blood supply* / Q000601:surgery; D008955:Models, Cardiovascular
keywords: 2D–3D Registration; Catheterization; Skeletonization; Subtree; Vascular structure model