Computer Vision News Computer Vision News 10 Anna adds: “Clinicians disagree so much on where exactly they want to segment these two areas. This is why it’s very important in this case for doctors to trust what the machine is doing and to introduce and model this uncertainty, so they don’t just have a black box where you have an input image and the output, but they have this pipeline, which is more insightful, and they have this uncertainty output in the end!” The probabilistic nature of the model acknowledges the inherent uncertainties in medical segmentation and diagnosis. It is important to model multiple possibilities so the doctor can do a second check and choose which segmentation to use. You get the best of both worlds with doctors and machines working together. Although this work is focused on medical imaging, the general applicability of the segmentation framework and leveraging uncertainty could extend beyond medical imaging. Segmentation is crucial in various fields, such as autonomous driving scenarios. The problem is strongly clinically inspired but not restricted to it. Winning the Best Poster award was a moment of pride for the team. “Of course, we’re all very happy!” Anna smiles. “We’re very grateful for the recognition of our work and happy that the way we presented it was easy to follow.” MIDL Best Poster Award Winner You get the best of both worlds with doctors and machines working together
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