88 citations · 165 across the 5 of their papers we have counts for
7 papers
Improved reproducibility of diffusion kurtosis imaging using regularized non-linear optimization informed by artificial neural networks
Leevi Kerkelä, Kiran Seunarine, Rafael Neto Henriques +2
Diffusion kurtosis imaging is an extension of diffusion tensor imaging that provides scientifically and clinically valuable information about brain tissue microstructure but suffer…
Evidence for microscopic kurtosis in neural tissue revealed by Correlation Tensor MRI
Rafael Neto Henriques, Sune Nørhøj Jespersen, Noam Shemesh
Purpose: The impact of microscopic diffusional kurtosis () - arising from restricted diffusion and/or structural disorder - remains a controversial issue in contemporary diffus…
Double diffusion encoding and applications for biomedical imaging
Rafael N. Henriques, Marco Palombo, Sune N. Jespersen +3
Diffusion Magnetic Resonance Imaging (dMRI) is one of the most important contemporary non-invasive modalities for probing tissue structure at the microscopic scale. The majority of…
Validation and noise robustness assessment of microscopic anisotropy estimation with clinically feasible double diffusion encoding MRI
Leevi Kerkelä, Rafael Neto Henriques, Matt G. Hall +2
Purpose: Double diffusion encoding (DDE) MRI enables the estimation of microscopic diffusion anisotropy, yielding valuable information on tissue microstructure. A recent study prop…
Fitting IVIM with Variable Projection and Simplicial Optimization
Shreyas Fadnavis, Hamza Farooq, Maryam Afzali +10
Fitting multi-exponential models to Diffusion MRI (dMRI) data has always been challenging due to various underlying complexities. In this work, we introduce a novel and robust fitt…
Correlation Tensor Magnetic Resonance Imaging
Rafael Neto Henriques, Sune Nørhøj Jespersen, Noam Shemesh
Diffusional Kurtosis Imaging (DKI) is a sensitive biomarker for microstructure in health and disease. However, DKI is not specific to any microstructural property since it may emer…