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

Area of Science:

• Surgical Technology
• Medical Imaging
• Computer-Assisted Surgery

Background:

• Augmented reality (AR) systems are increasingly used in minimally invasive surgery.
• Accurate image-to-patient registration is critical for the effectiveness of AR in laparoscopic liver resection.
• Point-based registration (PBR) is a common method for achieving this registration.

Purpose of the Study:

• To evaluate the accuracy of point-based registration (PBR) for augmented reality (AR) applications in laparoscopic liver resection.
• To assess the impact of varying target sampling accuracy on registration performance.

Main Methods:

• The study utilized three scenarios with decreasing target accuracy: a machined phantom, a patient-specific phantom, and an in vivo study.
• Target Registration Error (TRE) and Fiducial Registration Error (FRE) were calculated.
• Image-to-patient registration was performed using five randomly selected positions.

Main Results:

• Mean TRE was 6.9 mm for the machined phantom, 7.9 mm for the patient-specific phantom, and 13.4 mm in the in vivo setting.
• AR demonstrated increased TRE and FRE as target sampling accuracy decreased.
• The size of the registration volume influenced the observed errors.

Conclusions:

• Augmented reality systems are sensitive to the accuracy of target sampling in point-based registration.
• Reducing errors in target annotation and the size of registration volumes can enhance the robustness of AR systems in surgery.
• Further optimization is needed for reliable AR-guided laparoscopic liver resections.