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
Research Topics
Journal publications
In Press
“A preparation pulse for fast steady state approach in Actual Flip angle Imaging”, Medical Physics, In Press. ,
2023
“ImWIP: open-source image warping toolbox with adjoints and derivatives”, SoftwareX, vol. 24, p. 101524, 2023. ,
“dtiRIM: A generalisable deep learning method for diffusion tensor imaging”, Neuroimage, vol. 269, 2023.
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“Systematic review of reconstruction techniques for accelerated quantitative MRI”, Magnetic Resonance in Medicine, vol. 90, no. 3, pp. 1172-1208, 2023.
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“Use of support vector machines approach via ComBat harmonized diffusion tensor imaging for the diagnosis and prognosis of mild traumatic brain injury: a CENTER-TBI study”, Journal of Neurotrauma, 2023. ,
“Optimal experimental design and estimation for q-space trajectory imaging”, Human Brain Mapping, vol. 44, no. 4, pp. 1793-1809, 2023.
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“Prolonged microgravity induces reversible and persistent changes on human cerebral connectivity”, Communications Biology, vol. 6, no. 46, 2023. ,
“ADEPT: Accurate Diffusion EPI with multi-contrast shoTs”, Magnetic Resonance in Medicine, vol. 89, no. 1, pp. 396-410, 2023.
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2022
“Investigating tissue-specific abnormalities in Alzheimer’s disease with multi-shell diffusion MRI”, Journal of Alzheimer's Disease, vol. 90, no. 4, pp. 1771-1791, 2022. ,
“Model-based super-resolution reconstruction with joint motion estimation for improved quantitative MRI parameter mapping”, Computerized Medical Imaging and Graphics, vol. 100, no. 102071, pp. 1-16, 2022.
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