Computer Vision News - October 2021

43 Mert Sabuncu Best of MICCAI 2021 that sense. I view the healthcare and biomedicine domain as a very interesting area where we can make a strong impact and hopefully have a positive influence on many people’s lives. In my family, I have been surrounded by doctors and medical researchers from a very young age, and I guess that’s what first attracted me to biomedical research. Do you feel that the work that you and your team are doing, and the work that the MICCAI community is doing, is having that impact? I think that as a community what we do at MICCAI has a big impact. I also think that the research that comes out of my group has an impact in sometimes very non-obvious ways. It’s important to remind oneself that what we do can feel a little bit like basic research. A little bit removed from real-world applications. There are still some open questions that we need to work on before we can take our technologies and apply them to real-world problems. That said, as I move along my career trajectory, I’m hoping I will increase my emphasis on real-world translation. That’s why nowadays I’m focusing on real clinical collaborations and understanding clinical workflows. I’m hoping to put more effort into translating our technologies into the clinic, either by commercialization efforts, or at least trying to implement things in an academic hospital setting. Why does it take so long sometimes to translate MICCAI research into the clinic? There is always a gap. Whatever field you’re in, especially in the academic setting, there’s going to be a gap between the research and the way it impacts people’s lives in the real world. The healthcare world has a lot of stakeholders, including patients, insurance companies, regulatory bodies, hospitals, doctors, and researchers. Having them all aligned and getting through all their needs and requirements is a big challenge. Taking an idea from a concept to a real product that can be used in a clinical workflow on patients, there are a lot of obstacles along the way. The other challenge is as researchers on the algorithmic side, we often focus on toy problems. That is a good starting point but can be distracting in terms of what matters in the real world. We spend a lot of our bandwidth on these “artificial problems” and make good progress, but to take those breakthroughs and translate them into the real world, there are other challenges that we aren’t focusing on. There are obviously exceptions, but there’s not a lot of incentive, at least in the academic world, to move along those steps. A lot of those incentives are in the more basic research. Do you think today’s CLINNICAI, MICCAI’s first clinical day, is a step in the right direction? I think these types of ideas and especially communities like MICCAI make a difference. They enable different groups of people to communicate with each other to