Magnetic Resonance Imaging
Magnetic resonance imaging (MRI) is a biomedical imaging technique used to visualize detailed internal structures. The Quantitative MRI group of the Vision Lab develops novel reconstruction, processing and analysis algorithms to process anatomical, functional or diffusion-weighted MRI data. These methods rely on profound knowledge of the MR imaging principles. The core competence of the group is quantitative, statistical parameter estimation, which is the basis for developing novel techniques for image reconstruction, image denoising, higher order diffusion parameter estimation (DTI, DKI, ...), and fiber tractography.
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Journal publications
2014
“Data distributions in magnetic resonance images: a review”, Physica Medica, vol. 30, no. 7, pp. 725–741, 2014.
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“Isotropic non-white matter partial volume effects in constrained spherical deconvolution”, Frontiers in Neuroinformatics, vol. 8, pp. 1-9, 2014.
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“A new non local maximum likelihood estimation method for Rician noise reduction in Magnetic Resonance images using the Kolmogorov-Smirnov test”, Signal Processing, vol. 103, pp. 16-23, 2014. ,
2013
“Regional gray matter volume differences and sex-hormone correlations as a function of menstrual cycle phase and hormonal contraceptives use.”, Brain research, vol. 1530, pp. 22-31, 2013. ,
“Optimal estimation of diffusion MRI parameters”, 2013.
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“Increased coherence of white matter fiber tract organization in adults with Asperger syndrome: A diffusion tensor imaging study”, Autism Research, vol. 6, no. 6, pp. 642-650, 2013.
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“Discrete Tomography in MRI: a Simulation Study”, Fundamenta Informaticae, vol. 125, no. 3-4, pp. 223-237, 2013. ,
“Altered diffusion tensor imaging measurements in aged transgenic Huntington disease rats.”, Brain structure & function, vol. 218, no. 3, pp. 767-78, 2013.
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“Weighted linear least squares estimation of diffusion MRI parameters: Strengths, limitations, and pitfalls.”, NeuroImage, vol. 81, no. 1, pp. 335-346, 2013.
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“Subchronic memantine induced concurrent functional disconnectivity and altered ultra-structural tissue integrity in the rodent brain: revealed by multimodal MRI.”, Psychopharmacology, vol. 227, no. 3, pp. 479-91, 2013. ,