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.
People
Journal publications
2010
“Morphologic and functional changes in the unilateral 6-hydroxydopamine lesion rat model for Parkinson's disease discerned with microSPECT and quantitative MRI.”, Magnetic Resonance Materials in Physics, Biology and Medicine, vol. 23, no. 2, pp. 65-75, 2010. ,
“Noise measurement from magnitude MRI using local estimates of variance and skewness.”, Physics in medicine and biology, vol. 55, no. 16, pp. N441-9, 2010. Download paper (219.85 KB) ,
“A Machine Learning Study of Several Classifiers Trained with Texture Analysis Features to Differentiate Benign from Malignant Soft Tissue Tumors in T1-MRI Images”, Journal of Magnetic Resonance Imaging, vol. 31, pp. 680–689, 2010. Download paper (300.61 KB) ,
“Optimal experimental design for Diffusion Kurtosis Imaging”, IEEE Transactions on Medical Imaging, vol. 29, pp. 819-829, 2010. Download paper (1.12 MB) ,
“Correlation of cognitive dysfunction and diffusion tensor MRI measures in patients with mild and moderate multiple sclerosis”, Journal of magnetic resonance imaging, vol. 31, pp. 1492-1498, 2010. ,
“Diffusion tensor image up-sampling: a registration-based approach”, Magnetic resonance Imaging, vol. 28, pp. 1497-1506, 2010. Download paper (814.96 KB) ,
“Improved B0 field map estimation for high field EPI”, Magnetic Resonance Imaging, vol. 28, pp. 441-450, 2010. Download paper (1.29 MB) ,
“Comparing isotropic and anisotropic smoothing for voxel-based DTI analyses: A simulation study”, Human Brain Mapping, vol. 31, pp. 98-114, 2010. ,
2009
“A diffusion tensor imaging group study of the spinal cord in multiple sclerosis patients with and without T2 spinal cord lesions.”, Journal of magnetic resonance imaging : JMRI, vol. 30, no. 1, pp. 25-34, 2009. Download paper (902.67 KB) ,
“Diffusion tensor imaging in a rat model of Parkinson's disease after lesioning of the nigrostriatal tract.”, NMR in biomedicine, vol. 22, no. 7, pp. 697-706, 2009. ,