如何可视化脑肿瘤手术中影像导航的不确定性
Visualizing Uncertainty in Image Guided Surgery a Review
- 用定量方法评估术中脑组织变形带来的导航误差
- 提出将不确定度信息以直观图形方式呈现给医生
- 适合关注医学影像与人机交互的临床研究者
在肿瘤切除手术中，神经外科医生依赖术前影像（如MRI、超声）进行脑内导航，类似大脑的GPS。然而，由于渗透压变化、液体水平波动及组织切除等导致的脑移位，术前影像会失准，引发配准不确定性。有效量化并可视化这种不确定性，有助于重建医生对导航系统的信任。不确定性研究已有百年历史，其核心包含两个环节：一是对不确定性的量化，二是将量化结果传达给观察者。近年来，这两个方向均受到广泛关注。
原文摘要 · Abstract (English)
During tumor resection surgery, surgeons rely on neuronavigation to locate tumors and other critical structures in the brain. Most neuronavigation is based on preoperative images, such as MRI and ultrasound, to navigate through the brain. Neuronavigation acts like GPS for the brain, guiding neurosurgeons during the procedure. However, brain shift, a dynamic deformation caused by factors such as osmotic concentration, fluid levels, and tissue resection, can invalidate the preoperative images and introduce registration uncertainty. Considering and effectively visualizing this uncertainty has the potential to help surgeons trust the navigation again. Uncertainty has been studied in various domains since the 19th century. Considering uncertainty requires two essential components: 1) quantifying uncertainty; and 2) conveying the quantified values to the observer. There has been growing interest in both of these research areas during the past few decades.
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