Visualizing Uncertainty in Image Guided Surgery a Review
This is a review paper, so it is incremental, summarizing existing research on uncertainty visualization for neurosurgeons.
The paper reviews methods for visualizing uncertainty in image-guided brain surgery, addressing the problem of brain shift invalidating preoperative images and introducing registration uncertainty, with the goal of helping surgeons trust neuronavigation again.
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.