Visualizing Uncertainty in Image Guided Surgery a Review
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866910780624994304 |
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| author | Geshvadi, Mahsa |
| author_facet | Geshvadi, Mahsa |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_06280 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Visualizing Uncertainty in Image Guided Surgery a Review Geshvadi, Mahsa Computer Vision and Pattern Recognition Graphics 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. |
| title | Visualizing Uncertainty in Image Guided Surgery a Review |
| topic | Computer Vision and Pattern Recognition Graphics |
| url | https://arxiv.org/abs/2501.06280 |