Improved 2D/3D registration robustness using local spatial information

Elena De Momi; Kort Eckman; Branislav Jaramaz; Anthony DiGioia

doi:10.1117/12.654024

10 March 2006 Improved 2D/3D registration robustness using local spatial information

Elena De Momi, Kort Eckman, Branislav Jaramaz, Anthony DiGioia

Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 614431 (2006) https://doi.org/10.1117/12.654024
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

Xalign is a tool designed to measure implant orientation after joint arthroplasty by co-registering a projection of an implant model and a digitally reconstructed radiograph of the patient's anatomy with a post operative x-ray. A mutual information based registration method is used to automate alignment. When using basic mutual information, the presence of local maxima can result in misregistration. To increase robustness of registration, our research is aimed at improving the similarity function by modifying the information measure and incorporating local spatial information. A test dataset with known groundtruth parameters was created to evaluate the performance of this measure. A synthetic radiograph was generated first from a preoperative pelvic CT scan to act as the gold standard. The voxel weights used to generate the image were then modified and new images were generated with the CT rigidly transformed. The roll, pitch and yaw angles span a range of -10/+10 degrees, while x, y and z translations range from -10mm to +10mm. These images were compared with the reference image. The proposed cost function correctly identified the correct pose in all tests and did not exhibit any local maxima which would slow or prevent locating the global maximum.

Citation Download Citation

Elena De Momi, Kort Eckman, Branislav Jaramaz, and Anthony DiGioia "Improved 2D/3D registration robustness using local spatial information", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 614431 (10 March 2006); https://doi.org/10.1117/12.654024

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