19 citations · 23 across the 3 of their papers we have counts for
3 papers
Spherical convolutional neural networks can improve brain microstructure estimation from diffusion MRI data
Leevi Kerkelä, Kiran Seunarine, Filip Szczepankiewicz +1
Diffusion magnetic resonance imaging is sensitive to the microstructural properties of brain tissue. However, estimating clinically and scientifically relevant microstructural prop…
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…
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…