Influence of sampling accuracy on augmented reality for laparoscopic image-guided surgery

Abstract

Purpose

This study aims to evaluate the accuracy of point-based registration (PBR) when used for augmented reality (AR) in laparoscopic liver resection surgery.

Material and methods

The study was conducted in three different scenarios in which the accuracy of sampling targets for PBR decreases: using an assessment phantom with machined divot holes, a patient-specific liver phantom with markers visible in computed tomography (CT) scans and in vivo, relying on the surgeon’s anatomical understanding to perform annotations. Target registration error (TRE) and fiducial registration error (FRE) were computed using five randomly selected positions for image-to-patient registration.

Results

AR with intra-operative CT scanning showed a mean TRE of 6.9 mm for the machined phantom, 7.9 mm for the patient-specific phantom and 13.4 mm in the in vivo study.

Conclusions

AR showed an increase in both TRE and FRE throughout the experimental studies, proving that AR is not robust to the sampling accuracy of the targets used to compute image-to-patient registration. Moreover, an influence of the size of the volume to be register was observed. Hence, it is advisable to reduce both errors due to annotations and the size of registration volumes, which can cause large errors in AR systems.

Keywords:

• Image-guided surgery
• augmented reality
• target registration error
• laparoscopic surgery
• hand-eye calibration

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Acknowledgements

The authors would like to express their gratitude to all the OR team at ‘The Intervention Centre’, Oslo University Hospital.

Ethical approvals

All procedures performed in studies involving animals were in accordance with the ethical standards of the institution or practice at which the studies were conducted. This article does not contain any studies with human participants performed by any of the authors.

Declaration of interest

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

Additional information

Funding

This work was supported by H2020-MSCA-ITN Marie Skodowska-Curie Actions, Innovative Training Networks (ITN) 2016 GA EU project number 722068 High Performance Soft Tissue Navigation (HiPerNav).