Paper
18 March 2016 Non-rigid point set registration of curves: registration of the superficial vessel centerlines of the brain
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Abstract
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 (T1). Once the correspondences are known, the corresponding points are used to define a new TPS deformation(T2). The errors are measured in the deformed space, by transforming the original points using T1 and T2 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.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Filipe M. M. Marreiros, Chunliang Wang, Sandro Rossitti, and Örjan Smedby "Non-rigid point set registration of curves: registration of the superficial vessel centerlines of the brain", Proc. SPIE 9786, Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling, 978611 (18 March 2016); https://doi.org/10.1117/12.2208421
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KEYWORDS
Brain

Image registration

3D image processing

Image segmentation

Surgery

Distance measurement

Error analysis

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