5 Computer Vision News Computer Vision News SINR: Spline-enhanced implicit neural … measures to measure the performance. Also, we don’t really know what a possibly good result is in the end.” To tackle these challenges, she takes 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. This approach is helpful for registration because it allows for recovering transformations at different resolutions, including at sub-pixel levels. The inspiration for this approach came from prior work by Wolterink et al. at MIDL 2022, which applied INRs to lung registration. However, adapting this method to brain images revealed two major issues. “The first was that the transformation is smooth because inter-brain registration is more complicated than lung registration,” Vasiliki points out. “Then we saw that using these INRs, we have way more spatial folding, meaning that, for example, the space is in a state that it’s not usable anymore or produces illegal transformations, and then, the final result is not good enough. The second major thing we saw was that the way sampling of the coordinates was done, we weren’t able to do multi-modal registration with mutual information.” Vasiliki tells us these issues were somewhat expected, given that the registration field is progressing more slowly than other fields in
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