J
Jelle Veraart
Researcher at New York University
Publications - 91
Citations - 6211
Jelle Veraart is an academic researcher from New York University. The author has contributed to research in topics: Diffusion MRI & Diffusion Kurtosis Imaging. The author has an hindex of 33, co-authored 78 publications receiving 4600 citations. Previous affiliations of Jelle Veraart include University of Antwerp.
Papers
More filters
Journal ArticleDOI
Denoising of diffusion MRI using random matrix theory
Jelle Veraart,Dmitry S. Novikov,Daan Christiaens,Benjamin Ades-Aron,Jan Sijbers,Els Fieremans +5 more
TL;DR: A post-processing technique for fast denoising of diffusion-weighted MR images is introduced and it is demonstrated that the technique suppresses local signal fluctuations that solely originate from thermal noise rather than from other sources such as anatomical detail.
Journal ArticleDOI
Diffusion MRI noise mapping using random matrix theory.
TL;DR: To estimate the spatially varying noise map using a redundant series of magnitude MR images, a random number generator is used to estimate the signal-to- Noise ratio.
Journal ArticleDOI
Weighted linear least squares estimation of diffusion MRI parameters: Strengths, limitations, and pitfalls
TL;DR: If proper weighting strategies are applied, the weighted linear least squares approach shows high performance characteristics in terms of accuracy/precision and may even be preferred over nonlinear estimation methods.
Journal ArticleDOI
Gliomas: Diffusion Kurtosis MR Imaging in Grading
Sofie Van Cauter,Jelle Veraart,Jan Sijbers,Ronald R. Peeters,Uwe Himmelreich,Frederik De Keyzer,Stefaan Van Gool,Frank Van Calenbergh,Steven De Vleeschouwer,Wim Van Hecke,Stefan Sunaert +10 more
TL;DR: There were significant differences in kurtosis parameters between high-grade and low-grade gliomas; hence, better separation was achieved with these parameters than with conventional diffusion imaging parameters.
Journal ArticleDOI
Degeneracy in model parameter estimation for multi‐compartmental diffusion in neuronal tissue
TL;DR: The results suggest that theBiophysical interpretation of dMRI model parameters crucially depends on establishing which of the minima is closer to the biophysical reality and the size of the uncertainty associated with each parameter.