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Published in:
2020 | OriginalPaper | Chapter
Learning-Based Correspondence Estimation for 2-D/3-D Registration
Authors : Roman Schaffert, Markus Weiß, Jian Wang, Anja Borsdorf, Andreas Maier
Published in: Bildverarbeitung für die Medizin 2020
Publisher: Springer Fachmedien Wiesbaden
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In many minimally invasive procedures, image guidance using a C-arm system is utilized. To enhance the guidance, information from pre-operative 3-D images can be overlaid on top of the 2-D fluoroscopy and 2-D/3-D image registration techniques are used to ensure an accurate overlay. Despite decades of research, achieving a highly reliable registration remains challenging. In this paper, we propose a learning-based correspondence estimation, which focuses on contour points and can be used in combination with the point-to-plane correspondence model-based registration. When combined with classical correspondence estimation in a refinement step, the method highly increases the robustness, leading to a capture range of 36mm and a success rate of 98.5%, compared to 14mm and 71.9% for the purely classical approach, while maintaining a high accuracy of 0.430.08mm of mean re-projection distance.