27 Improved PCNL with Computer Vision Computer Vision News itself. Additionally, computer vision can merge two images taken with fluoroscopy and provide 3D information: what would be complicate for the mind is made much easier by mathematical formulas. When we have additional external hardware like electromagnetic trackers (EMT) or optical trackers, we can add this information and compute the position of the needle, even when it is not clearly visible in the image itself. We can also fuse all this information to provide additional assistance to the surgeon. If the needle is beneath the ultrasound plane, this info will guide the surgeon to point the ultrasound probe in a better direction. AI algorithm should be the work of expert engineers: providing correct information to the surgeon is a major concern and any misleading info about the exact location of the needle is potentially dangerous. AI and the surgeon do not replace one another: they should complement each other and work together. The key contribution of AI is in the detection of relevant anatomical structure and the needle, in the mathematical formulas for 3D fusion and in the combination of 3D data coming from external sources, like an EMT or Multiview fluoroscopy images. More articles about AI for Urology. Contact RSIP Vision to learn more.
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