# Computer Vision-Based Navigation System for High-Precision Orthopedic Trauma Surgery

> **NIH NIH R21** · JOHNS HOPKINS UNIVERSITY · 2020 · $204,688

## Abstract

PROJECT SUMMARY / ABSTRACT
Closed or open fracture reduction and internal fixation is the standard surgical approach in treating pelvic fractures, with
current clinical practice using fluoroscopic guidance, guidewire insertion, and cannulated screw placement. The
challenge in reckoning complex 3D morphology in 2D fluoroscopy presents a major source of uncertainty, trial-and-
error, and poor outcomes, with 20-30% rate of suboptimal screw placement and long fluoroscopic runtime (mean fluoro
time > 123 s) exposing operating personnel to high levels of radiation exposure. Despite these challenges, mainstream
surgical approach has remained largely unchanged for 35 years, and surgical navigation systems (though increasingly
common in neurosurgery) present cost and workflow barriers that limit their broad applicability in trauma surgery.
We propose a computer vision-based navigation approach that is compatible with routine trauma surgery workflow,
offers real-time guidance with accuracy comparable to stereotactic navigation, gives ten-fold reduction in radiation
exposure, and works with tools already common in the trauma surgery arsenal. The proposed system uses a miniature
stereoscopic camera mounted onboard the surgical drill in combination with 3D-2D registration of fluoroscopic views for
direct, real-time registration of the instrument trajectory relative to patient anatomy. Real-time overlay of instrument
trajectory in fluoroscopic views and/or CT permits accurate identification of guidewire entry point, orientation, and
conformance within bone corridors and will reduce reliance on “fluoro hunting” and trial-and-error guidewire
placement. The following aims develop and evaluate the system for application in pelvic trauma surgery, including
quantitative assessment of accuracy, workflow, and radiation dose in pre-clinical studies.
Aim 1. System for computer vision-based guidance in trauma surgery. The hardware and software components
required for vision-based tracking onboard a standard surgical drill will be developed, providing real-time trajectory
overlay in fluoroscopy and/or preoperative CT. A fast calibration method will be developed for automatic drill axis
calibration. Automatic feature-based registration of the video and fluoroscopic frames enables real-time overlay of
instrument trajectory in fluoroscopic views (Fluoro Navigation), and 3D-2D registration between CT and fluoroscopy will
enable real-time overlay of the instrument trajectory in CT (CT Navigation).
Aim 2: Evaluation in preclinical studies. The vision-based navigation system will be implemented in pre-clinical
(cadaver) experiments to evaluate accuracy and workflow. These studies will evaluate the geometric accuracy and
workflow factors relating to the number of repeated insertion attempts, procedure time, and radiation dose, evaluating
vision-based Fluoro Navigation and CT Navigation in comparison to conventional freehand fluoroscopy guidance.
Successful completion of the aims ...

## Key facts

- **NIH application ID:** 10005337
- **Project number:** 5R21EB028330-02
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** JEFFREY H SIEWERDSEN
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $204,688
- **Award type:** 5
- **Project period:** 2019-09-01 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10005337

## Citation

> US National Institutes of Health, RePORTER application 10005337, Computer Vision-Based Navigation System for High-Precision Orthopedic Trauma Surgery (5R21EB028330-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10005337. Licensed CC0.

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