Segmentation of X-ray Images by 3D-2D Registration Based on Multibody Physics
X-ray imaging is commonly used in clinical routine. In radiotherapy, spatial information is extracted from X-ray images to correctly position patients before treatment. Similarly, orthopedic surgeons assess the positioning and migration of implants after Total Hip Replacement (THR) with X-ray images. However, the projective nature of X-ray imaging hinders the reliable extraction of rigid structures in X-ray images, such as bones or metallic components. We developed an approach based on multibody physics that simultaneously registers multiple 3D shapes with one or more 2D X-ray images. Considered as physical bodies, shapes are driven by image forces, which exploit image gradient, and constraints, which enforce spatial dependencies between shapes. Our method was tested on post-operative radiographs of THR and thoroughly validated with gold standard datasets. The final target registration error was in average \(0.3\pm 0.16\) mm and the capture range improved more than 40 % with respect to reference registration methods.
KeywordsBlock Match Target Registration Error World Coordinate System Statistical Shape Model Compute Tomography Volume
This work is funded by the Swiss CTI project MyHip (no. 13573.1). Authors would like to thank E. Ambrosetti, J. Marquis and the MyHip consortium. The CT and Xray images and gold standard registration were provided by the Laboratory of Imaging Technologies, University of Ljubljana, Slovenia  and the Image Sciences Institute, Utrecht, Netherlands .
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