Abstract
2D-3D image registration is an important task for computer-aided minimally invasive vascular therapies. A crucial component for practical image registration is the use of multilevel strategies to avoid local optima and to speed-up runtime. However, due to the different dimensionalities of the 2D fixed and 3D moving image, the setup of multilevel strategies is not straightforward. In this work, we propose an intensity-driven 2D-3D multiresolution registration approach using the normalized gradient fields (NGF) distance measure. We discuss and empirically analyze the impact on the choice of 2D and 3D image resolutions. Furthermore, we show that our approach produces results that are comparable or superior to other state-of-the-art methods.
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CITATION STYLE
Lange, A., & Heldmann, S. (2020). Multilevel 2d-3d intensity-based image registration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12120 LNCS, pp. 57–66). Springer. https://doi.org/10.1007/978-3-030-50120-4_6
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