Computer Vision News - August 2020

What unexpected changes will you make in the next ten years? I actually don’t know! If you ask me: “Where do I see myself in ten years?” , I would say: “I don’t know!” What would you like to happen? I don’t know. Come on: you are doing a very difficult job, in a very difficult setting, working with things that have a huge impact on mankind. You still don’t have any hopes or dreams for the next ten years? I’m sure that you have some inner motivation that you are hiding from us. I’m not hiding anything! [ laughs ] There is a lot of research going on right now in the community, a lot of smart people with amazing ideas. I would love to see a lot of these ideas actually make it to the point of care for patients. So that it does not stopwith this abstract idea and initial experiments. I would love to see it go a little bit further so that it actually reaches the end customer. That’s actually one of the reasons that I really appreciate my job right now. My motivation is usually to learn. What I learn right now is all of the different perspectives. It takes a lot of effort and different points of view to actually bring an idea to the market and to the patient. I discuss with, not only researchers now, but also doctors and IT from hospitals. Now that we know your inner motivation, we would like to learn what is the main problem in healthcare now that prevents science from bringing all that it develops straight to the patient? One pain point right now is the dataset. Research is driven by datasets. We did the statistics on MICCAI last year. Only a fraction of the papers, only 10% or something, did not use AI somehow in their research. Sometimes it's the main method. Sometimes it's a block in the pipeline. But everyone uses some AI. Most of the AI algorithms are actually driven by centralized datasets. As I mentioned before, there are a lot of publications out there where these datasets exist. One of the bottlenecks is the availability of datasets that can foster research. I’m not only complaining about that. I’m trying to work on this myself! Find more than 100 interviews of brilliant female scientists here! Nicola Rieke 43 Best of MIDL 2020 “I would love to see a lot of these ideas actually make it to the point of care for patients.” 1