Computer Vision News Computer Vision News 6 “…a novel approach using implicit neural representations (INRs). These multi-layer perceptron networks with periodic activation functions or positional encodings offer a compressed and continuous representation of signals!” medical imaging, such as segmentation or super-resolution. Could this be why the work caught the eyes of the judges at MIDL? “I think the motivation of the work was clear, and the solution was easy to grasp,” she considers. “We saw other interesting works at MIDL, but this was the major difference. It was probably easy for everybody to understand, and the presentation was good, so that’s why we won.” The study’s success is also a testament to the collaborative efforts and mentorship within the research group, including from Vasiliki’s main supervisor, Daniel Rueckert, and Magdalini Paschali, both dear friends of this magazine. “Daniel is an expert in registration,” she tells us. “Back in the day, he worked a lot in the registration and segmentation field, and I think this expertise from the pre-deep learning era is valuable. All these old papers and ideas can become new if you treat them the right way.” Vasiliki met Magda during her master’s thesis while working with Walter Simson in Nassir Navab’s group. “Magda is very good at organizing ideas,” she says. “Taking an idea from A and bringing it to B. That’s very useful because, at some point in a project, you don’t know where you are and need somebody to put everything in the right place.” Vasiliki was born in Greece and studied there for her bachelor’s and first master’s before moving to Germany for her second master’s. Reflecting on her journey, she highlights the supportive research environment in Germany, where she found people with similar interests and an easier environment in which to work. “In Greece, the situation is MIDL Best Oral Paper Award Winner
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