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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Zuber, Marcus
in Cooperation with on an Cooperation-Score of 37%
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Publications (7/7 displayed)
- 2023A comparative study of conservation methods for waterlogged wood - a review of the 'Cutaway' project
- 2022Tofu: a fast, versatile and user-friendly image processing toolkit for computed tomographycitations
- 2022Inverted Hartmann mask made by deep X-ray lithography for single-shot multi-contrast X-ray imaging with laboratory setupcitations
- 2022Inverted Hartmann mask made by deep X-ray lithography for single-shot multi-contrast X-ray imaging with laboratory setupcitations
- 2021Assessing the microstructure and in vitro degradation behavior of Mg-xGd screw implants using µCTcitations
- 2021Morphological determinants of bite force capacity in insects: a biomechanical analysis of polymorphic leaf-cutter antscitations
- 2017Large-area full field x-ray differential phase-contrast imaging using 2D tiled gratingscitations
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article
Tofu: a fast, versatile and user-friendly image processing toolkit for computed tomography
Abstract
<jats:p><jats:italic>Tofu</jats:italic> is a toolkit for processing large amounts of images and for tomographic reconstruction. Complex image processing tasks are organized as workflows of individual processing steps. The toolkit is able to reconstruct parallel and cone beam as well as tomographic and laminographic geometries. Many pre- and post-processing algorithms needed for high-quality 3D reconstruction are available, <jats:italic>e.g.</jats:italic> phase retrieval, ring removal and de-noising. <jats:italic>Tofu</jats:italic> is optimized for stand-alone GPU workstations on which it achieves reconstruction speed comparable with costly CPU clusters. It automatically utilizes all GPUs in the system and generates 3D reconstruction code with minimal number of instructions given the input geometry (parallel/cone beam, tomography/laminography), hence yielding optimal run-time performance. In order to improve accessibility for researchers with no previous knowledge of programming, <jats:italic>tofu</jats:italic> contains graphical user interfaces for both optimization of 3D reconstruction parameters and batch processing of data with pre-configured workflows for typical computed tomography reconstruction. The toolkit is open source and extensive documentation is available for both end-users and developers. Thanks to the mentioned features, <jats:italic>tofu</jats:italic> is suitable for both expert users with specialized image processing needs (<jats:italic>e.g.</jats:italic> when dealing with data from custom-built computed tomography scanners) and for application-specific end-users who just need to reconstruct their data on off-the-shelf hardware.</jats:p>