Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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693.932 PEOPLE
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Zuber, Marcus

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (7/7 displayed)

  • 2023A comparative study of conservation methods for waterlogged wood - a review of the 'Cutaway' projectcitations
  • 2022Tofu: a fast, versatile and user-friendly image processing toolkit for computed tomography84citations
  • 2022Inverted Hartmann mask made by deep X-ray lithography for single-shot multi-contrast X-ray imaging with laboratory setup3citations
  • 2022Inverted Hartmann mask made by deep X-ray lithography for single-shot multi-contrast X-ray imaging with laboratory setup3citations
  • 2021Assessing the microstructure and in vitro degradation behavior of Mg-xGd screw implants using µCT31citations
  • 2021Morphological determinants of bite force capacity in insects: a biomechanical analysis of polymorphic leaf-cutter ants55citations
  • 2017Large-area full field x-ray differential phase-contrast imaging using 2D tiled gratings16citations

Places of action

Chart of shared publication
Wittköpper, Markus
1 / 1 shared
Schuetz, Philipp
1 / 6 shared
Heinz, Guido
1 / 1 shared
Martinez Garcia, Jorge
1 / 4 shared
Egg, Markus
1 / 1 shared
Stelzner, Jörg
1 / 3 shared
Gwerder, Damian
1 / 2 shared
Cramer, Anja
1 / 1 shared
Stelzner, Ingrid
1 / 2 shared
Muskalla, Waldemar
1 / 1 shared
Zakharova, Margarita
2 / 6 shared
Khanda, Ankita
2 / 5 shared
Vlnieska, Vitor
2 / 11 shared
Mikhaylov, Andrey
2 / 3 shared
Bremer, Sabine
2 / 2 shared
Kunka, Danays
3 / 9 shared
Pezzin, Sergio Henrique
1 / 2 shared
Moosmann, Julian
1 / 20 shared
Zeller-Plumhoff, Berit
1 / 20 shared
Wieland, Florian
1 / 6 shared
Willumeit, Regine
1 / 9 shared
Krueger, Diana
1 / 1 shared
Wiese, Bjoern
1 / 5 shared
Yi, Sangbong
1 / 12 shared
Tietze, Sabrina
1 / 1 shared
Engelhardt, Sabine
1 / 1 shared
Reichert, Klaus-Martin
1 / 2 shared
Schröter, Tobias J.
1 / 1 shared
Hofmann, Andreas
1 / 2 shared
Koch, Frieder J.
1 / 1 shared
Meyer, Pascal
1 / 3 shared
Willer, Konstantin
1 / 1 shared
Birnbacher, Lorenz
1 / 1 shared
Mohr, Jürgen
1 / 2 shared
Prade, Friedrich
1 / 2 shared
Pfeiffer, Franz
1 / 5 shared
Baumbach, Tilo
1 / 15 shared
Chart of publication period
2023
2022
2021
2017

Co-Authors (by relevance)

  • Wittköpper, Markus
  • Schuetz, Philipp
  • Heinz, Guido
  • Martinez Garcia, Jorge
  • Egg, Markus
  • Stelzner, Jörg
  • Gwerder, Damian
  • Cramer, Anja
  • Stelzner, Ingrid
  • Muskalla, Waldemar
  • Zakharova, Margarita
  • Khanda, Ankita
  • Vlnieska, Vitor
  • Mikhaylov, Andrey
  • Bremer, Sabine
  • Kunka, Danays
  • Pezzin, Sergio Henrique
  • Moosmann, Julian
  • Zeller-Plumhoff, Berit
  • Wieland, Florian
  • Willumeit, Regine
  • Krueger, Diana
  • Wiese, Bjoern
  • Yi, Sangbong
  • Tietze, Sabrina
  • Engelhardt, Sabine
  • Reichert, Klaus-Martin
  • Schröter, Tobias J.
  • Hofmann, Andreas
  • Koch, Frieder J.
  • Meyer, Pascal
  • Willer, Konstantin
  • Birnbacher, Lorenz
  • Mohr, Jürgen
  • Prade, Friedrich
  • Pfeiffer, Franz
  • Baumbach, Tilo
OrganizationsLocationPeople

article

Tofu: a fast, versatile and user-friendly image processing toolkit for computed tomography

  • Zuber, Marcus
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>

Topics
  • impedance spectroscopy
  • cluster
  • phase
  • tomography