Multi-body registration for fracture reduction in orthopaedic trauma surgery

R. Han, A. Uneri, P. Wu, R. Vijayan, P. Vagdargi, M. Ketcha, N. Sheth, S. Vogt, G. Kleinszig, G. M. Osgood, J. H. Siewerdsen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


Purpose. Fracture reduction is a challenging part of orthopaedic pelvic trauma procedures, resulting in poor long-term prognosis if reduction does not accurately restore natural morphology. Manual preoperative planning is performed to obtain target transformations of target bones - a process that is challenging and time-consuming even to experts within the rapid workflow of emergent care and fluoroscopically guided surgery. We report a method for fracture reduction planning using a novel image-based registration framework. Method. An objective function is designed to simultaneously register multi-body bone fragments that are preoperatively segmented via a graph-cut method to a pelvic statistical shape model (SSM) with inter-body collision constraints. An alternating optimization strategy switches between fragments alignment and SSM adaptation to solve for the fragment transformations for fracture reduction planning. The method was examined in a leave-one-out study performed over a pelvic atlas with 40 members with two-body and three-body fractures simulated in the left innominate bone with displacements ranging 0-20 mm and 0°-15°. Result. Experiments showed the feasibility of the registration method in both two-body and three-body fracture cases. The segmentations achieved Dice coefficient of median 0.94 (0.01 interquartile range [IQR]) and root mean square error (RMSE) of 2.93 mm (0.56 mm IQR). In two-body fracture cases, fracture reduction planning yielded 3.8 mm (1.6 mm IQR) translational and 2.9° (1.8° IQR) rotational error. Conclusion. The method demonstrated accurate fracture reduction planning within 5 mm and shows promise for future generalization to more complicated fracture cases. The algorithm provides a novel means of planning from preoperative CT images that are already acquired in standard workflow.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2020
Subtitle of host publicationImage-Guided Procedures, Robotic Interventions, and Modeling
EditorsBaowei Fei, Cristian A. Linte
ISBN (Electronic)9781510633971
StatePublished - 2020
EventMedical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling - Houston, United States
Duration: Feb 16 2020Feb 19 2020

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


ConferenceMedical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling
Country/TerritoryUnited States


  • Image registration
  • Image segmentation
  • Image-guided surgery
  • Orthopaedic trauma
  • Statistical shape model

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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