MICCAI 2020 Daily - Tuesday

2 Workshop Preview 16 Patricia Johnson is a postdoc at NYU Langone Health in the US, Tobias Würfl is a staff researcher at Siemens Healthineers, and Jong Chul Ye is a professor at the Korea Advanced Institute of Science and Technology (KAIST). They are three of the organizers of Thursday’s third international workshop on Machine Learning for Medical Image Reconstruction (MLMIR). With two keynotes and 15 accepted papers across a wide range of topics, it is sure to be an exciting event. They speak to us about what to expect. “ Reconstruction is an integral part of the hardware of many imaging modalities,” Tobias explains . “It is a mathematically well-understood and rigorous topic where we can bring a lot of theory to bear, which is why I find it so fascinating. It is about solving an inverse problem, with hidden parameters which can only be accessed through measurements that do not show them directly. The goal of reconstruction generally is to infer those hidden parameters from the indirect measurements. Machine learning helps us to solve this problemby adding a prior, which is an expectation about what the reconstructed data should look like.” Machine Learning for Medical Image Reconstruction (MLMIR) Patricia Johnson Tobias Würfl Jong Chul Ye DAILY Tu e s d a y

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