research themes

Biomedical image analysis

Theory and computational methods related to the following:
  • Measures of Förster resonance energy transfer (FRET) efficiency to determine protein-protein interactions.
  • FRET imaging SNR measures.
  • Similarity metrics for medical image alignment.
  • Non-rigid geometrical transformations for image registration.
  • Information theory, in particular mutual information for solving non-linear mapping problems.
  • Methods to model and quantify deformation by non-rigid image alignment.
  • Serial MR brain image registration
  • MR geometrical distortion
  • Radial basis functions for interpolation and deformation modelling.
  • Fourier domain and scattered data interpolation.
  • Optical flow, fast convergent optical flow, and optical flow based motion boundary detection.
  • Multi-resolution, multi-scale image processing algorithms.
  • Theory of uncertainty and error propagation.
  • Theory, measurement and correction of geometric distortion in three dimensional magnetic resonance images.
  • Medical image segmentation based on expectation maximisation.
  • Laplacian based measures of the thickness brain structures from medical images.
  • Bayesian analysis, e.g. for image classification.
  • Fluorescence microscopy, Magnetic resonance imaging.
  • Algorithms for texture-based image classification based on a back-propagation of a multi-layer perceptron models.
  • Image analysis related

  • Stereo image matching algorithms.
  • Parallel algorithms for stereo image matching, comparative evaluation of parallel architectures.
  • Parallel architectures/systems (especially distributed memory processor arrays).
  • Parallel algorithms for image processing