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Forget Pixels: Adaptive Particle Representation of Fluorescence Microscopy Images

View ORCID ProfileBevan L. Cheeseman, View ORCID ProfileUlrik Günther, Mateusz Susik, View ORCID ProfileKrzysztof Gonciarz, View ORCID ProfileIvo F. Sbalzarini
doi: https://doi.org/10.1101/263061
Bevan L. Cheeseman
1Chair of Scientific Computing for Systems Biology, Faculty of Computer Science, TU Dresden, 01069 Dresden, Germany
2Center for Systems Biology Dresden, Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr. 108, 01307 Dresden, Germany
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  • For correspondence: ivos@mpi-cbg.de cheesema@mpi-cbg.de
Ulrik Günther
1Chair of Scientific Computing for Systems Biology, Faculty of Computer Science, TU Dresden, 01069 Dresden, Germany
2Center for Systems Biology Dresden, Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr. 108, 01307 Dresden, Germany
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Mateusz Susik
1Chair of Scientific Computing for Systems Biology, Faculty of Computer Science, TU Dresden, 01069 Dresden, Germany
2Center for Systems Biology Dresden, Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr. 108, 01307 Dresden, Germany
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Krzysztof Gonciarz
1Chair of Scientific Computing for Systems Biology, Faculty of Computer Science, TU Dresden, 01069 Dresden, Germany
2Center for Systems Biology Dresden, Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr. 108, 01307 Dresden, Germany
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Ivo F. Sbalzarini
1Chair of Scientific Computing for Systems Biology, Faculty of Computer Science, TU Dresden, 01069 Dresden, Germany
2Center for Systems Biology Dresden, Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr. 108, 01307 Dresden, Germany
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  • For correspondence: ivos@mpi-cbg.de cheesema@mpi-cbg.de
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Abstract

Modern microscopy modalities create a data deluge with gigabytes of data generated each second, or terabytes per day. Storing and processing these data is a severe bottleneck. We argue that this is an artifact of the images being represented on pixels. To address the root of the problem, we here propose the Adaptive Particle Representation (APR) as an image-content-aware representation of fluorescence microscopy images. The APR replaces pixel images to overcome computational and memory bottlenecks in storage and processing pipelines for studying spatiotemporal processes in biology using fluorescence microscopy. We present the ideas, concepts, and algorithms and validate them using noisy 3D image data. We show how the APR adapts to the information content of an image without reducing image quality. We then show that the adaptivity of the APR provides orders of magnitude benefits across a range of image-processing tasks. Therefore, the APR provides a simple, extendable, and efficient content-aware representation of images that could be useful for many imaging modalities in order to relax current data and processing bottlenecks.

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Posted February 09, 2018.
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Forget Pixels: Adaptive Particle Representation of Fluorescence Microscopy Images
Bevan L. Cheeseman, Ulrik Günther, Mateusz Susik, Krzysztof Gonciarz, Ivo F. Sbalzarini
bioRxiv 263061; doi: https://doi.org/10.1101/263061
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Forget Pixels: Adaptive Particle Representation of Fluorescence Microscopy Images
Bevan L. Cheeseman, Ulrik Günther, Mateusz Susik, Krzysztof Gonciarz, Ivo F. Sbalzarini
bioRxiv 263061; doi: https://doi.org/10.1101/263061

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