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Research project

AdvanCT - Advanced Computed Tomography for Dimensional and Surface Measurements in Industry


Lead researcher

Professor Thomas Blumensath


Research interests

  • I develop and study advanced algorithms that can solve challenging inverse problems by efficiently exploiting complex prior information. Using techniques from mathematics, statistics and machine learning, my work concentrates primarily on problems in x-ray tomographic image reconstruction and modelling.
  • I work closely with state-of-the-art imaging facilities (µ-VIS, the National Research Facility in Lab-based XCT, the UK’s synchrotron facility at the Diamond Light Source, and ISIS neutron imaging beamline) to find practical solutions to a range of important scientific problems from plant science to manufacturing.
  • My research interests cover areas such as: Theoretical and computational methods for Signal and Image Processing (Machine Learning, Compressed Sensing, Statistical Signal and Image Processing, Quantum Computing, Inverse Problems, Optimisation, X-ray Tomographic Imaging); Advanced tomographic imaging strategies: (limited angle tomography and laminography, Spectral X-ray imaging, Stereo and extreme limited view tomography); Efficient computational methods for tomographic reconstruction, including GPU acceleration, distributed computation and advanced optimisation strategies, Constrained optimisation for ill-conditioned and underdetermined   tomographic inverse problems, Applications of X-ray tomography to the inspection of manufactured components, Multimodal tomographic imaging

Connect with Thomas

Other researchers

Professor John Mcbride

Professor of Electro-Mechanical Eng

Connect with John

Collaborating research institutes, centres and groups

Research outputs

Harry Rossides,
Hossein Towsyfyan,
Ander Biguri,
Hans P Deyhle,
Reuben J Lindroos,
Mark Mavrogordato,
Richard Boardman,
Wenjuan Sun,
, 2022 , Metrologia , 59 (044003)
Type: article
Hans Deyhle,
Hossein Towsyfyan,
Ander Biguri,
Mark Mavrogordato,
& Thomas Blumensath
, 2020 , NDT & E International , 111
Type: article
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