Abstract

BackgroundMinimally invasive spine surgery is dependent on accurate navigation. Computer-assisted navigation is increasingly used in minimally invasive surgery (MIS), but current solutions require the use of reference markers in the surgical field for both patient and instruments tracking.PurposeTo improve reliability and facilitate clinical workflow, this study proposes a new marker-free tracking framework based on skin feature recognition.MethodsMaximally Stable Extremal Regions (MSER) and Speeded Up Robust Feature (SURF) algorithms are applied for skin feature detection. The proposed tracking framework is based on a multi-camera setup for obtaining multi-view acquisitions of the surgical area. Features can then be accurately detected using MSER and SURF and afterward localized by triangulation. The triangulation error is used for assessing the localization quality in 3D.ResultsThe framework was tested on a cadaver dataset and in eight clinical cases. The detected features for the entire patient datasets were found to have an overall triangulation error of 0.207 mm for MSER and 0.204 mm for SURF. The localization accuracy was compared to a system with conventional markers, serving as a ground truth. An average accuracy of 0.627 and 0.622 mm was achieved for MSER and SURF, respectively.ConclusionsThis study demonstrates that skin feature localization for patient tracking in a surgical setting is feasible. The technology shows promising results in terms of detected features and localization accuracy. In the future, the framework may be further improved by exploiting extended feature processing using modern optical imaging techniques for clinical applications where patient tracking is crucial.

Highlights

  • Invasive spine surgery is dependent on accurate navigation

  • This study demonstrates that skin feature localization for patient track‐ ing in a surgical setting is feasible

  • The framework may be further improved by exploiting extended feature processing using modern optical imaging techniques for clinical applications where patient tracking is crucial

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Summary

Introduction

Invasive spine surgery is dependent on accurate navigation. Computer-assisted navigation is increasingly used in minimally invasive surgery (MIS), but current solutions require the use of reference markers in the surgical field for both patient and instruments tracking.Purpose: To improve reliability and facilitate clinical workflow, this study proposes a new marker-free tracking framework based on skin feature recognition. Invasive spine surgery is dependent on accurate navigation. Computer-assisted navigation is increasingly used in minimally invasive surgery (MIS), but current solutions require the use of reference markers in the surgical field for both patient and instruments tracking. Invasive surgery (MIS) is performed through small skin incisions where the vertebrae are reached by use of tubular retractors [2]. Efforts have been made to design patient tracking methods based on unobtrusive markers or no markers at all One such system using non-invasive optical markers has been described by Malham et al [9, 10] (SpineMask, Stryker, Kalamazoo, Michigan, USA). The navigation technology used in this study is an augmented-reality surgical navigation (ARSN) system relying on adhesive optical skin markers for motion tracking and compensation [16, 17]. Direct tracking of spine features and tracking of skin features using hyperspectral cameras for spine surgery have recently been proven feasible

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