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Keyhole-aware laparoscopic augmented reality
DOI:10.1016/j.media.2024.103161.png)
摘要
En 中文
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.
Keyword:
Augmented reality
Endoscopy
Liver
Surgical guidance
期刊
IF:
11.8
论文数:
3.8K
被引数:
2.4W
机构
引用论文
Combining Visual Cues with Interactions for 3D-2D Registration in Liver Laparoscopy将视觉提示与交互作用相结合,在肝腹腔镜检查中进行3D-2D配准
The International Position on Laparoscopic Liver Surgery The Louisville Statement, 2008
ANNALS OF SURGERY
IF6.4
RANDOM SAMPLE CONSENSUS - A PARADIGM FOR MODEL-FITTING WITH APPLICATIONS TO IMAGE-ANALYSIS AND AUTOMATED CARTOGRAPHY随机样本共识-模型拟合的范例,可应用于图像分析和自动制图
Detection, segmentation, and 3D pose estimation of surgical tools using convolutional neural networks and algebraic geometry
MEDICAL IMAGE ANALYSIS
IF11.8

