Description

Leader of the group Computational Imaging: Joost Batenburg.

 

Our research group is developing the next generation of 3D imaging – enabling scientists to look further into objects of all kinds. Based on mathematics, algorithms and numerical solution techniques, our approach is interdisciplinary, combining aspects of mathematics, computer science and physics. We pride ourselves on the versatility of our solutions, and our algorithms can be applied to a wide range of imaging in science, medicine and industry. In Computational Imaging, it’s our goal to constantly push the boundaries of research. By combining advanced image acquisition, parameter estimation, and discrete tomography algorithms for example, we are able to develop workflows for 3D electron microscopy at atomic resolution.

 

 

Vacancies

No vacancies currently.

News

Making the invisible visible

Making the invisible visible

CT machines are becoming the standard tool for looking inside objects of all kinds in research and industry. The FleX-ray Lab at CWI is making this type of imaging more accessible to math and computer science researchers. It's also drawing interest from the art, history, and the social sciences community.

Making the invisible visible - Read More…

Making the invisible visible

Making the invisible visible

CT machines are becoming the standard tool for looking inside objects of all kinds in research and industry. The FleX-ray Lab at CWI is making this type of imaging more accessible to math and computer science researchers. It's also drawing interest from the art, history, and the social sciences community.

Making the invisible visible - Read More…

Members

Associated Members

Publications

Software

Current projects with external funding

  • Mathematics and Algorithms for 3D Imaging of Dynamic Processes ()
  • Non-destructive 3D spectral imaging: applications in the poultry industry ()
  • Real-Time 3D Tomography ()
  • Cervical Disease Maps
  • CT for Art: from Images to Patterns (IMPACT4Art)
  • MUltiscale, Multimodal and Multidimensional imaging for EngineeRING (MUMMERING)
  • Translation-Driven Development of Deep Learning for Simultaneous Tomographic Image Reconstruction and Segmentation (None)
  • Deep learning and compressed sensing for ultrasonic nondestructive testin (PPS Applus RTD)
  • Universal Three-dimensiOnal Passport for process Individualization in Agriculture (UTOPIA)
  • Enabling X-ray CT based Industry 4.0 process chains by training Next Generation research experts (xCTing)

Related partners

  • Fraunhofer Gesellschaft
  • Naturalis
  • Rijksmuseum Amsterdam
  • Universiteit Wageningen
  • University of Cambridge
  • GREEFA
  • Katholieke Universiteit Leuven
  • Rheinisch-Westfaelische Technische Hochschule Aachen
  • Universiteit Utrecht