Vision Lab - University of Antwerp

The university of Antwerp has a number of strong poles for the scientific research in biomedical and material sciences which make intensive use of research techniques involving image acquisition and analysis. Grouping of the present expertise by a multidisciplinar approach could strongly improve the effectivity of the research. Also for the theoretical mathematical and physical support for the development and implementation of image processing algorithms a broad competency is present in the University of Antwerp.

To be able to group this competence, the VISION LAB was founded at the end of 1991 by Prof. Dr. D. Van Dyck of the physics department. The aim is to expand the VISION LAB to a centre of excellence in the field of image processing where all research groups using images can profit by.

Research areas:

• MEDICAL IMAGE PROCESSING
  • MR image processing
    • SNR: quantification and improvement
    • 3D Segmentation
    • Parameter estimation
    • fMRI data processing
    • Diffusion tensor image processing
    • Tractography, brain connectivity estimation
    • Q-ball imaging
  • Computer tomography
    • Discrete tomography
    • Region of Interest Tomography
    • Segmentation
      • Thresholding of tomograms
      • Airway segmentation in CT images
    • Greylevel estimation for discrete tomography
    • Tomography on the GPU
    • Tomographic reconstruction with neural networks
  • Image registration
  • Mammography characterisation: Automated detection of microcalcifications
  • Voice characterisation
  • Multimodal image registration, fusion, merging




• IMAGE PROCESSING AND ANALYSIS
  • Segmentation
  • Restoration and artifact reduction
  • Voxel based morphometry
  • Pattern recognition, handwritten character recognition, fuzzy logic, cluster classification and information theory.
  • Color image quantization
  • High-dimensional clustering and feature extraction
  • Wavelet-Based Texture- and color classification
  • Multispectral Image Fusion and Classification
  • Spherical and cylindrical parameterization
  • Shape modelling and characterization
    • Airway modelling




• BIOCHEMISTRY
  • Electrophoresis




• COMPUTATIONAL PHYSICS
  • Statistical Methods: Hidden markov models, neural networks and statistical inference.
  • Computer Simulation: Models of physical and mathematical systems using C/C++, Mathematica and Matlab.




• MATERIALS SCIENCES
  • Material characterisation : (corrosion images, micro-crystals,...)
  • Corrosion Characterisation
  • AgX microcrystal characterisation
  • Shape of AgX Microcrystals