Non-rigid point set registration of curves: registration of the superficial vessel centerlines of the brain

被引:0
|
作者
Marreiros, Filipe M. M. [1 ,4 ,5 ]
Wang, Chunliang [1 ,2 ]
Rossitti, Sandro [3 ]
Smedby, Orjan [1 ,2 ,5 ]
机构
[1] Linkoping Univ, Ctr Med Image Sci & Visualizat CMIV, S-58183 Linkoping, Sweden
[2] Royal Inst Technol KTH, Sch Technol & Hlth, Huddinge, Sweden
[3] Country Council Ostergotland, Dept Neurosurg, Linkoping, Sweden
[4] Linkoping Univ, Media & Informat Technol, Dept Sci & Technol ITN, S-58183 Linkoping, Sweden
[5] Linkoping Univ, Dept Med & Hlth Sci IMH, S-58183 Linkoping, Sweden
关键词
Non-rigid registration; brain shift correction; vessel registration; SHIFT; VALIDATION; ALGORITHM;
D O I
10.1117/12.2208421
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
In this study we present a non-rigid point set registration for 3D curves (composed by 3D set of points). The method was evaluated in the task of registration of 3D superficial vessels of the brain where it was used to match vessel centerline points. It consists of a combination of the Coherent Point Drift (CPD) and the Thin-Plate Spline (TPS) semilandmarks. The CPD is used to perform the initial matching of centerline 3D points, while the semilandmark method iteratively relaxes/slides the points. For the evaluation, a Magnetic Resonance Angiography (MRA) dataset was used. Deformations were applied to the extracted vessels centerlines to simulate brain bulging and sinking, using a TPS deformation where a few control points were manipulated to obtain the desired transformation (T-1). Once the correspondences are known, the corresponding points are used to define a new TPS deformation(T-2). The errors are measured in the deformed space, by transforming the original points using T-1 and T-2 and measuring the distance between them. To simulate cases where the deformed vessel data is incomplete, parts of the reference vessels were cut and then deformed. Furthermore, anisotropic normally distributed noise was added. The results show that the error estimates (root mean square error and mean error) are below 1 mm, even in the presence of noise and incomplete data.
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页数:8
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