基准标记
计算机视觉
人工智能
医学
导航系统
增强现实
计算机科学
重射误差
影像引导手术
图像配准
病人登记
机械人手术
放射科
图像(数学)
作者
Egidijus Pelanis,Andrea Teatini,Benjamin Eigl,Alois Regensburger,Amilcar Alzaga,Rahul Prasanna Kumar,Tobias Rudolph,Davit L. Aghayan,Carina Riediger,Niclas Kvarnström,Ole Jakob Elle,Bjørn Edwin
标识
DOI:10.1016/j.media.2020.101946
摘要
In laparoscopic liver resection, surgeons conventionally rely on anatomical landmarks detected through a laparoscope, preoperative volumetric images and laparoscopic ultrasound to compensate for the challenges of minimally invasive access. Image guidance using optical tracking and registration procedures is a promising tool, although often undermined by its inaccuracy. This study evaluates a novel surgical navigation solution that can compensate for liver deformations using an accurate and effective registration method. The proposed solution relies on a robotic C-arm to perform registration to preoperative CT/MRI image data and allows for intraoperative updates during resection using fluoroscopic images. Navigation is offered both as a 3D liver model with real-time instrument visualization, as well as an augmented reality overlay on the laparoscope camera view. Testing was conducted through a pre-clinical trial which included four porcine models. Accuracy of the navigation system was measured through two evaluation methods: liver surface fiducials reprojection and a comparison between planned and navigated resection margins. Target Registration Error with the fiducials evaluation shows that the accuracy in the vicinity of the lesion was 3.78±1.89 mm. Resection margin evaluations resulted in an overall median accuracy of 4.44 mm with a maximum error of 9.75 mm over the four subjects. The presented solution is accurate enough to be potentially clinically beneficial for surgical guidance in laparoscopic liver surgery.
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