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Inertia based filtering of high resolution images using a GPU cluster

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Computing and Visualization in Science

Abstract

The scheme of inertia based anisotropic diffusion is a very powerful noise reducing and structure preserving image processing operator. This paper presents an implementation of this time consuming filter process on a cluster of Nvidia Tesla high performance computing processors, which can be applied to very large amounts of data in only a few minutes. Applying the inertia based diffusion filter to high resolution image stacks of neuron cells provides fully automatic geometric reconstructions of these images on a scale of <1μm. Such a high throughput and automatic image processing tool has great impact on various research areas, in particular the fast growing field of computational neuroscience, where one encounters increasing amount of microscopy data that needs to be processed.

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Authors and Affiliations

  1. Goethe-Center for Scientific Computing (G-CSC), Goethe-University, Kettenhofweg 139, 60325, Frankfurt am Main, Germany

    Daniel Jungblut, Gillian Queisser & Gabriel Wittum

Authors
  1. Daniel Jungblut
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  2. Gillian Queisser
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  3. Gabriel Wittum
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Correspondence to Daniel Jungblut.

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Communicated by Martin Rumpf.

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Jungblut, D., Queisser, G. & Wittum, G. Inertia based filtering of high resolution images using a GPU cluster. Comput. Visual Sci. 14, 181–186 (2011). https://doi.org/10.1007/s00791-012-0171-2

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  • DOI: https://doi.org/10.1007/s00791-012-0171-2

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