锁孔
增强现实
计算机视觉
管道(软件)
计算机科学
人工智能
可视化
成像体模
职位(财务)
投影(关系代数)
计算机图形学(图像)
放射科
医学
算法
焊接
材料科学
财务
经济
冶金
程序设计语言
作者
Yamid Espinel,Navid Rabbani,Thien Bao Bui,Mathieu Ribeiro,Emmanuel Buc,Adrien Bartoli
标识
DOI:10.1016/j.media.2024.103161
摘要
Augmented Reality (AR) from preoperative data is a promising approach to improve intraoperative tumour localisation in Laparoscopic Liver Resection (LLR). Existing systems register the preoperative tumour model with the laparoscopic images and render it by direct camera projection, as if the organ were transparent. However, a simple geometric reasoning shows that this may induce serious surgeon misguidance. This is because the tools enter in a different keyhole than the laparoscope. As AR is particularly important for deep tumours, this problem potentially hinders the whole interest of AR guidance. A remedy to this issue is to project the tumour from its internal position to the liver surface towards the tool keyhole, and only then to the camera. This raises the problem of estimating the tool keyhole position in laparoscope coordinates. We propose a keyhole-aware pipeline which resolves the problem by using the observed tool to probe the keyhole position and by showing a keyhole-aware visualisation of the tumour. We assess the benefits of our pipeline quantitatively on a geometric in silico model and on a liver phantom model, as well as qualitatively on three patient data.
科研通智能强力驱动
Strongly Powered by AbleSci AI