Computer Vision News Computer Vision News 36 Moving from video or stereo imaging to a single image has several advantages. It greatly simplifies the procedure for the surgeon, who can focus on the operation at hand without needing to perform specific movements or capture images from multiple angles. The software handles all the necessary computations. As well as being widely applicable, it is also an effective tool for real-time surgical decision-making. In the kidney stone example, the surgeon can click on two points in the image, get the position of each, and calculate the distance between them. If this is smaller than a defined threshold, the surgeon will get an indication and can make an informed choice about whether to extract the stone or continue to break it up. Training the algorithms behind this innovative technology requires a substantial amount of data. A combination of real and simulated data is often used to develop and refine these models. “Simulations give us a very good ground truth,” Arik advises. “There are several variants. Some train a complex model with synthetic data, which works quite well on real cases and is then used to train a smaller model. Some train on a mix of real and synthetic cases. In all cases, simulated data is critical to the training data. Once we have ground truth, using simulated or real data, this already fits a regular flow of training deep neural networks.” While this technology holds immense promise, it is still relatively new and needs to be tested against the ground truth in real-world cases. For these experiments, stones that have been removed will need to be measured for their actual size and compared against their computed measurements from videos. Ultimately, the hope is that the technology will be widely adopted in medical practice, giving surgeons a powerful new way to analyze 3D structures and make critical decisions during procedures. If you think we could help with your project, contact RSIP Vision today for an informal discussion about your work. Deep Learning by RSIP Vision
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