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.

 

 

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Associated Members

Publications

Software

Current projects with external funding

  • Machine learning for large 3D tomographic images ()
  • Non-destructive 3D spectral imaging: applications in the poultry industry ()
  • Rapid 3D Printing through full-field volumetric photolithography ()
  • Real-Time 3D Tomography ()
  • Mathematics and Algorithms for 3D Imaging of Dynamic Processes
  • PPS contract Planmeca
  • CT for Art: from Images to Patterns (IMPACT4Art)
  • Combining cycloidal computed tomography with machine learning: a mechanism to disrupt the costly relationship between spatial resolution and radiation dose (ML-CYCLO-CT)
  • MUltiscale, Multimodal and Multidimensional imaging for EngineeRING (MUMMERING)
  • Deep learning and compressed sensing for ultrasonic nondestructive testin (PPS Applus RTD)
  • Volumetric medical x-ray imaging at extremely low dose (VOXEL)

Related partners

  • Centre National de la Recherche Scientifique (CNRS), Gif-sur-Yvette, France
  • CNR Pisa
  • COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES
  • IMAGINE OPTIC
  • Naturalis
  • Planmeca
  • Rijksmuseum Amsterdam
  • Universidad Politécnica de Madrid
  • Photosynthetic B.V.
  • University College London