The Open Bioinformatics Foundation (OBF) Event Fellowship program aims to promote diverse participation at events promoting open source bioinformatics software development and open science practices in the biological research community. Pengfei Fan, a researcher from Queen Mary University of London, was supported to participate in CLEO 2020 by this fellowship granted to him in the application round-1 of 2020. Find more information here.
During the last two decades, we are witnessing a fascinating growth of computational imaging (CI) methods, e.g. tomography, compressive sensing and 3D/super-resolved/lensless microscopy, and artificial intelligence (AI) algorithms, mainly machine learning and deep learning, both from the theoretical (mathematical) and practical (experimental) point of view. New computational capabilities in terms of, e.g., big data, large scale optimisation, neural networks and highly parallel computing, are facilitating further improvements in numerically enhanced imaging surpassing the limitations imposed by ‘classical’ all-optical information processing systems. It is joyful to observe how CI and AI merge to innovatively address challenging tasks fuelled by wide-spreading applications in 3D imaging, biomedicine, microscopy and general physics of light propagation in scattering media, to name just a few. When designing a computational imaging technique, one needs to originally link the applicable data acquisition scheme with the capable image reconstruction algorithm, often aided by learning-based frameworks employed not only for image classification and interpretation but also for image formation and final outcome restoration. As the AI stimulatory development continues to flourish, open-source tools and software, especially deep learning framework and platform, have become a key ingredient of modern science. Hundreds of software packages, libraries, and applications have become essential tools.
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