27 DAILY MICCAI Tuesday Mirabela, how did you get so many appointments? Well, because my work is very interdisciplinary. The goal of my team is to improve the interpretation of radiology images. We work a lot with prostate cancer, and that places us from radiology to urology. But we are data scientists, so why not also have a foot in the data science space? What are the things that you're doing, and why could they be useful? Very good question! We are working on helping radiologists and clinicians with the interpretation of radiology images. We do this because we really believe that AI approaches can work hand in hand with these clinicians and address some of the shortcomings of their own interpretation of these images, which is what's known as the standard of care. That's pretty much where we go. But we have collaborations that are very active in the space of urology because we're working on prostate cancer. We think of this as being a lowhanging fruit. And it has something to do with the fact that when I started in science, the things that I work on a lot have been registering multimodal data. I actually started with biomedical data. So, it's not really medical, but more biological structural biology. I come from a background of all these techniques that are what we now consider preprocessing techniques. They really are essential for labeling data for AI approaches. So, we build on that expertise that I have accumulated over maybe 15 years of doing science. Nowit’s like, okay, we can develop AI approaches. We can create these labels that nobody has or has taken advantage of. As a team, we focus a lot on not just having yet another study that develops one of these preprocessing techniques but actually taking them to the next step. So, if I say yes, we are going to use registration to align radiology and pathology data, my science doesn't stop at the paper that shows how we do this. My focus is to take this and do the next step, which is labels. Now, let's start training. Let's see what are the advantages and disadvantages of this. A lot of your speech is plural, and you talked about a team. There are also other people. Tell us about that. We have a very diverse team. I run my lab in collaboration with a urologist, Geoff Sonn, an associate professor in the urology department. 50% of the people are in my lab, and 50% are in his lab. But practically speaking, he's a clinician. He doesn't really have time for basic research or AI research. We want to make sure that by working together, we take advantage of the complementary expertise that we have. So that's my other clinical half. But then, together, we are leading this team. Mirabela Rusu
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