37 Computer Vision News Calibration Techniques for Node Classification ... Does she have any thoughts on what it was about her work this time that convinced the judges to commend it so highly? “I don’t know for sure, but I feel it’s becauseit’s not that mathematically complex or innovative; it’s just an application,” she ponders. “MIDL focuses a lot on reproducibility and scientific impact, and this study is quite easy for other scientists to get some information out of and get some take-home message and then apply some techniques. We also put the code online for the benchmark dataset, so it’s reproducible. But yeah, I was still surprised!” Iris’s supervisor on this work, Hugo Kuijf, should already be familiar to readers of this magazine. She tells us his philosophy is that PhDs should be hard work but also fun. “It felt more like a collaboration than that he was my supervisor,” she recalls. “We got along really well. He taught me a lot about supervising students and how to best motivate a student that’s not doing well. He’s really good in his communication, in his soft skills.” Looking ahead, she is focused on mesh neural networks, a novel approach in medical image data analysis, aiming to identify patterns in vascular structures across individuals to identify different subgroups with varying risks for aneurysm development. Also, combining different fields to obtain the best model – for example, CNNs or meshes with graphs. “In the end, we want to obtain a personalized risk model for each patient,” Iris reveals. “Then, based on that model, we can see if we should perform follow-up screening and how often. This way, we hope to detect aneurysms in an early stage so they can be treated before causing damage.” Iris with the other award winners at MIDL 2023
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