ArticleMedical image analysis2021
Fracture reduction planning and guidance in orthopaedic trauma surgery via multi-body image registration.
Article in Medical image analysis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- How Can Technology Improve Acetabular and Pelvic Fractures Management in the Operating Room? A Systematic Review.Orthopaedic surgery · 2026Pooled it
- Anatomy-driven automated subsegmentation of pelvic and proximal femoral CT into clinically relevant subregions and landmarks.BMC medical imaging · 2026Article
- Emerging Technologies for Assisted Fracture Reduction: A Systematic Review.Annals of biomedical engineering · 2026Review
- An automated method for precise definition of fracture reduction targets.Medical & biological engineering & computing · 2026Article
- Patient-specific musculoskeletal modeling to enhance preoperative planning for pelvic fracture reduction.Communications medicine · 2025Article
- Robot-assisted versus conventional percutaneous screw fixation in calcaneal fractures: a retrospective analysis.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2025Review
- 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
- PelviNet: A Collaborative Multi-agent Convolutional Network for Enhanced Pelvic Image Registration.Journal of imaging informatics in medicine · 2025Article
- Computer-aided robotics for applications in fracture reduction surgery: Advances, challenges, and opportunities.iScience · 2025Review
- Automatic pelvic fracture segmentation: a deep learning approach and benchmark dataset.Frontiers in medicine · 2025Article
- An End-to-End Geometry-Based Pipeline for Automatic Preoperative Surgical Planning of Pelvic Fracture Reduction and Fixation.IEEE transactions on medical imaging · 2025Article
- Clinical validation of artificial intelligence-based preoperative virtual reduction for Neer 3- or 4-part proximal humerus fractures.BMC musculoskeletal disorders · 2024Article
- Experimental research based on robot-assisted surgery: Lower limb fracture reduction surgery planning navigation system.Health science reports · 2024Article
- Automatic segmentation of inconstant fractured fragments for tibia/fibula from CT images using deep learning.Scientific reports · 2023Article
- Semi-Supervised Medical Image Segmentation Guided by Bi-Directional Constrained Dual-Task Consistency.Bioengineering (Basel, Switzerland) · 2023Article
- Multi-Body 3D-2D Registration for Robot-Assisted Joint Reduction: Preclinical Evaluation in the Ankle Syndesmosis.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- Technologies evolution in robot-assisted fracture reduction systems: a comprehensive review.Frontiers in robotics and AI · 2023Review
- An Experimental Study of a 3D Bone Position Estimation System Based on Fluoroscopic Images.Diagnostics (Basel, Switzerland) · 2022Article
- Computer-assisted preoperative planning of bone fracture fixation surgery: A state-of-the-art review.Frontiers in bioengineering and biotechnology · 2022Review
Corrections and comments
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Authors and funding
10 authors.
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Abstract
purposesSurgical reduction of pelvic fracture is a challenging procedure, and accurate restoration of natural morphology is essential to obtaining positive functional outcome. The procedure often requires extensive preoperative planning, long fluoroscopic exposure time, and trial-and-error to achieve accurate reduction. We report a multi-body registration framework for reduction planning using preoperative CT and intraoperative guidance using routine 2D fluoroscopy that could help address such challenges.
methodThe framework starts with semi-automatic segmentation of fractured bone fragments in preoperative CT using continuous max-flow. For reduction planning, a multi-to-one registration is performed to register bone fragments to an adaptive template that adjusts to patient-specific bone shapes and poses. The framework further registers bone fragments to intraoperative fluoroscopy to provide 2D fluoroscopy guidance and/or 3D navigation relative to the reduction plan. The framework was investigated in three studies: (1) a simulation study of 40 CT images simulating three fracture categories (unilateral two-body, unilateral three-body, and bilateral two-body); (2) a proof-of-concept cadaver study to mimic clinical scenario; and (3) a retrospective clinical study investigating feasibility in three cases of increasing severity and accuracy requirement.
resultsSegmentation of simulated pelvic fracture demonstrated Dice coefficient of 0.92±0.06. Reduction planning using the adaptive template achieved 2-3 mm and 2-3° error for the three fracture categories, significantly better than planning based on mirroring of contralateral anatomy. 3D-2D registration yielded ~2 mm and 0.5° accuracy, providing accurate guidance with respect to the preoperative reduction plan. The cadaver study and retrospective clinical study demonstrated comparable accuracy: ~0.90 Dice coefficient in segmentation, ~3 mm accuracy in reduction planning, and ~2 mm accuracy in 3D-2D registration.
conclusionThe registration framework demonstrated planning and guidance accuracy within clinical requirements in both simulation and clinical feasibility studies for a broad range of fracture-dislocation patterns. Using routinely acquired preoperative CT and intraoperative fluoroscopy, the framework could improve the accuracy of pelvic fracture reduction, reduce radiation dose, and could integrate well with common clinical workflow without the need for additional navigation systems.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.