Welcome to Vision Lab - University of Antwerp
iMinds - Vision Lab
The Vision Lab is a research lab of the Department of Physics of the University of Antwerp. Vision Lab's main research area is the development of novel image reconstruction, processing and analysis methods, which are applied in the domain of Tomography, Magnetic Resonance Imaging, Shape modelling, and Remote Sensing. Since its foundation in 1992, about 20 PhD's have been defended and 7 spin-off companies have been founded. Latest spin-off: IcoMetrix.
Tomography is an imaging technique in which a 3D image of an object or patient is reconstructed from a series of 2D projection images. At the Vision Lab, novel reconstruction methods for tomography are developed and applied on all scales and imaging modalities, ranging from electron microsocopy, preclinical research, and medical research to industrial CT.
Magnetic Resonance Imaging
Magnetic resonance imaging (MRI) is a medical imaging technique used to visualize detailed internal structures. In the Vision Lab, the processing and analysis of anatomical, functional and diffusion-weighted MRI data is being studied. Topics of research include the development of techniques for image denoising, image reconstruction, statistical data modeling, parameter estimation, higher order diffusion modeling and fiber tractography.
Shape Modeling targets the description of the shape variation present in a population of scans with so called 'statistical shape models'. A major challenge in building shape models is finding correspondences between the scans. At the Vision Lab, correspondence methods based on surface parameterization and surface registration are researched. Next to the fundamental research, Vision Lab also focuses on applying shape models for improving fit and function of products that are worn close to or in the human body..
Remote Sensing is the research area in which earth's surface is studied, usually using the reflectance spectrum of the sun. Vision Lab 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 are vegetation monitoring for which we collaborate with the Teleprocessing group of VITO (Flemish Institute for Technological Research).
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