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The development of fast and accurate reconstruction algorithms is a central mathematical aspect of imaging. Most traditional image reconstruction methods can basically be classified in either analytical or iterative methods. Recently, a new class of image reconstruction methods appeared which use methods from machine learning, especially from deep learning. Initial results using deep learning techniques for image reconstruction demonstrate great promise, for example, for improving image quality, reducing computation time, or reducing radiation exposure. In this minisymposium leading experts will report on recent progress towards using machine learning for image reconstruction.