Fiducial-free 2D/3D registration of the proximal femur for robot-assisted femoroplasty
Abstract
Femroplasty is a proposed therapeutic method for preventing osteoporotic hip fractures in elderly. Patientspecific femoroplasty based on a preoperative plan, however, requires accurate 3D pose estimation of the proximal femur. Prior work on the development of a navigation system required the attachment of an optical fiducial to the osteoporotic femur. In this paper, we propose a fiducial-free 2D/3D registration pipeline, which uses the pelvis to initialize the femur registration. Intraoperative X-ray images are taken from multiple views to perform compound object registration. The proposed method was tested through a comprehensive simulation study. Performance was evaluated on the femoral head center frame registration error and the injection entry point error on the trochanter surface. The algorithm achieved a mean accuracy of 2.75 ± 2.19 mm for the entry point ℓ2 distance and 0.81 ± 0.58° for the planning path direction, which is sufficiently accurate for robotic drill positioning.
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The CMAES benchmark method for pose estimation of bone anatomy and surgical devices has been tested to meet clinical requirements in various orthopedic applications.
“Due to its well-known robustness to local minima, the CMAES benchmark method for pose estimation of bone anatomy and surgical devices has been tested to meet clinical requirements in various orthopedic applications, including osteotomy [2], [13], femoroplasty [41], [4], core decompression of the hip [42], and transforaminal lumbar epidural injections [43], etc.”
From A Fully Differentiable Framework for 2D/3D Registration and the Projective Spatial Transformers (2024) · cites this paper as [41]
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Unberath, M., Gao, C., Hu, Y., Judish, M., Taylor, R. H., Armand, M., & Grupp, R. (2021) · Frontiers in Robotics and AI · doi:10.3389/frobt.2021.716007 · Cited by 102 · see citing works
“The above traditional approach to solving 2D/3D image registration has spawned solutions that precisely recover the desired geometric transformations under certain conditions [15, 17, 18, 19].”
BackgroundMethodInfluentialSelf-citationAutomatic Annotation of Hip Anatomy in Fluoroscopy for Robust and Efficient 2D/3D Registration
Grupp, R. B., Unberath, M., Gao, C., Hegeman, R. A., Murphy, R. J., Alexander, C. P., Otake, Y., McArthur, B. A., Armand, M., & Taylor, R. H. (2020) · International Journal of Computer Assisted Radiology and Surgery · doi:10.1007/s11548-020-02162-7 · Cited by 81 · see citing works
“The automated annotation and registration techniques proposed in this paper could streamline intraoperativeworkflows related to intact hip anatomy, such as osteotomy planning [8], robotic drilling [31], and 3D reconstructions of bone [32] or implanted tracking fiducials [33].”
MethodSelf-citationA Fully Differentiable Framework for 2D/3D Registration and the Projective Spatial Transformers
Gao, C., Feng, A., Liu, X., Taylor, R. H., Armand, M., & Unberath, M. (2024) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2023.3299588 · Cited by 36 · see citing works
“…method for pose estimation of bone anatomy and surgical devices has been tested to meet clinical requirements in various orthopedic applications, including osteotomy [2], [13], femoroplasty [4], [41], core decompression of the hip [42], and transforaminal lumbar epidural injections [43], etc.”
MethodSelf-citation
- Authors
- Gao, C., Grupp, R. B., Unberath, M., Taylor, R. H., & Armand, M.
- Affiliations
- Johns Hopkins University (US)
- Venue
- Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling
- Publisher
- SPIE
- Published
- 2020-03-16
- Pages
- 47
- OpenAlex
- W3010754154
- Cited by
- 14
- References
- 0
- Citations by year
- 2025: 2 · 2023: 4 · 2022: 2 · 2021: 4 · 2020: 2
- FWCI
- 0.93
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- SPIE Medical Imaging: Image-Guided Procedures, Robotic Interventions, and Modeling (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Health Sciences › Medicine › Epidemiology › Bone fractures and treatments
- Health Sciences › Medicine › Surgery › Spinal Fractures and Fixation Techniques
- Keywords
- femoroplasty, 2D-3D registration, robotic surgery, surgical planning
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