ArticlePhysics in medicine and biology2020
Multi-body 3D-2D registration for image-guided reduction of pelvic dislocation in orthopaedic trauma surgery.
Article in Physics in medicine and biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 26 citations in OpenAlex.
- An automated method for precise definition of fracture reduction targets.Medical & biological engineering & computing · 2026Article
- LL-MAROCO: A Large Language Model-Assisted Robotic System for Oral and Craniomaxillofacial Osteotomy.Bioengineering (Basel, Switzerland) · 2025Article
- Shape-matching-based fracture reduction aid concept exemplified on the proximal humerus-a pilot study.International journal of computer assisted radiology and surgery · 2025Article
- Robot-Assisted Reduction of the Ankle Joint via Multi-Body 3D-2D Image Registration.IEEE transactions on medical robotics and bionics · 2024Article
- Intelligent robot-assisted fracture reduction system for the treatment of unstable pelvic fractures.Journal of orthopaedic surgery and research · 2024Article
- Comparison of 3D Bone Position Estimation Using QR Code and Metal Bead Markers.Diagnostics (Basel, Switzerland) · 2023Article
- An Experimental Study of a 3D Bone Position Estimation System Based on Fluoroscopic Images.Diagnostics (Basel, Switzerland) · 2022Article
- Preclinical evaluation of a prototype freehand drill video guidance system for orthopedic surgery.Journal of medical imaging (Bellingham, Wash.) · 2022Article
- Design and evaluation of an intelligent reduction robot system for the minimally invasive reduction in pelvic fractures.Journal of orthopaedic surgery and research · 2022Article
- Fracture reduction planning and guidance in orthopaedic trauma surgery via multi-body image registration.Medical image analysis · 2021Article
- Drill-mounted video guidance for orthopaedic trauma surgery.Journal of medical imaging (Bellingham, Wash.) · 2021Article
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Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
Abstract
Surgical reduction of pelvic dislocation is a challenging procedure with poor long-term prognosis if reduction does not accurately restore natural morphology. The procedure often requires long fluoroscopic exposure times and trial-and-error to achieve accurate reduction. We report a method to automatically compute the target pose of dislocated bones in preoperative CT and provide 3D guidance of reduction using routine 2D fluoroscopy. A pelvic statistical shape model (SSM) and a statistical pose model (SPM) were formed from an atlas of 40 pelvic CT images. Multi-body bone segmentation was achieved by mapping the SSM to a preoperative CT via an active shape model. The target reduction pose for the dislocated bone is estimated by fitting the poses of undislocated bones to the SPM. Intraoperatively, multiple bones are registered to fluoroscopy images via 3D-2D registration to obtain 3D pose estimates from 2D images. The method was examined in three studies: (1) a simulation study of 40 CT images simulating a range of dislocation patterns; (2) a pelvic phantom study with controlled dislocation of the left innominate bone; (3) a clinical case study investigating feasibility in images acquired during pelvic reduction surgery. Experiments investigated the accuracy of registration as a function of initialization error (capture range), image quality (radiation dose and image noise), and field of view (FOV) size. The simulation study achieved target pose estimation with translational error of median 2.3 mm (1.4 mm interquartile range, IQR) and rotational error of 2.1° (1.3° IQR). 3D-2D registration yielded 0.3 mm (0.2 mm IQR) in-plane and 0.3 mm (0.2 mm IQR) out-of-plane translational error, with in-plane capture range of ±50 mm and out-of-plane capture range of ±120 mm. The phantom study demonstrated 3D-2D target registration error of 2.5 mm (1.5 mm IQR), and the method was robust over a large dose range, down to 5 [Formula: see text]Gy/frame (an order of magnitude lower than the nominal fluoroscopic dose). The clinical feasibility study demonstrated accurate registration with both preoperative and intraoperative radiographs, yielding 3.1 mm (1.0 mm IQR) projection distance error with robust performance for FOV ranging from 340 × 340 mm
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