Medical Image Processing

Medical imaging processing represent a unique and highly specialized discipline that is critical for high-quality imaging research.

The vision Lab supports medical imaging processing by it's three sub divisions:

  • The QMRI group's core expertise comprises the quantification of magnetic resonance imaging (MRI) parameters with focus on diffusion weighted MRI. Ground-breaking methodologies are developed for reconstruction, processing and parameter estimation, based on expert knowledge of the MRI imaging model. The developed methods are applied in neuro-imaging to study various processes such as neurodegeneration, neuroregeneration, or neuroplasticity.
  • The ASTRA group, (All Scale Tomographic Reconstruction Antwerp), has unique expertise in computational aspects of computed tomography (CT). Whereas most tomography research takes place within specific application fields, such as medical imaging or materials science, ASTRA focuses on the underlying general reconstruction problems that are shared between these applications. The developed methods are applied in X-ray imaging, phase contrast imaging, electron microscopy, SPECT, THz and X-ray CT. 
  • The SI (Spectral Imaging) group on spectral imaging has built expertise in the processing and analysis of multispectral and hyperspectral remote sensing images. Topics of research include the development of techniques for image denoising, restoration, fusion, segmentation, classification and spectral unmixing. Main application domains of the SI technologies are vegetation monitoring for which they collaborate with the Teleprocessing group of VITO (Flemish Institute for Technological Research) and non-destructive testing (e.g. corrosion detection).

Since 2018, Vision Lab is officially accredited as research group of imec, the world-leading R&D and innovation hub in nanoelectronics and digital technologies. Within this organization, Vision Lab conducts interdisciplinary basic research with other research groups and industrial partners.

 

DKI MRI atlas project