Investigating the accuracy of machine vision and augmented reality in percutaneous computed tomography-guided interventions: A phantom study.

Abstract

This study aimed to evaluate the accuracy of percutaneous computed tomography (CT)-guided puncture based on machine vision and augmented reality in a phantom. The surgical space coordinate system was established, and accurate registration was ensured using the hierarchical optimization framework. Machine vision tracking and augmented reality display technologies were used for puncture navigation. CT was performed on a phantom, and puncture paths with three different lengths were planned from the surface of the phantom to the metal ball. Puncture accuracy was evaluated by measuring the target positioning error (TPE), lateral error (LE), angular error (AE), and first success rate (FSR) based on the obtained CT images. A highly qualified attending interventional physician performed a total of 30 punctures using puncture navigation. For the short distance (4.5-5.5 cm), the TPE, LE, AE, and FSR were 1.90 ± 0.62 mm, 1.23 ± 0.70 mm, 1.39 ± 0.86°, and 60%, respectively. For the medium distance (9.5-10.5 cm), the TPE, LE, AE, and FSR were 2.35 ± 0.95 mm, 2.00 ± 1.07 mm, 1.20 ± 0.62°, and 40%, respectively. For the long distance (14.5-15.5 cm), the TPE, LE, AE, and FSR were 2.81 ± 1.17 mm, 2.33 ± 1.34 mm, 0.99 ± 0.55°, and 30%, respectively. The augmented reality and machine vision-based CT-guided puncture navigation system allows for precise punctures in a phantom. Further studies are needed to explore its clinical applicability.