4 papers
Eddeep: a deep-learning framework for fast eddy-current distortion correction in diffusion MRI
Antoine Legouhy, Ross Callaghan, Yuchuan Qiao +4
Diffusion MRI (dMRI) relies on diffusion-weighted echo-planar imaging, which is highly susceptible to eddy-current-induced geometric distortions. These distortions vary across diff…
Polaffini: A feature-based approach for robust affine and polyaffine image registration
Antoine Legouhy, Cosimo Campo, Ross Callaghan +2
In this work we present Polaffini, a robust and versatile framework for anatomically grounded registration. Medical image registration is dominated by intensity-based registration…
NimbleReg: A light-weight deep-learning framework for diffeomorphic image registration
Antoine Legouhy, Ross Callaghan, Nolah Mazet +3
This paper presents NimbleReg, a light-weight deep-learning (DL) framework for diffeomorphic image registration leveraging surface representation of multiple segmented anatomical r…
Eddeep: Fast eddy-current distortion correction for diffusion MRI with deep learning
Antoine Legouhy, Ross Callaghan, Whitney Stee +3
Modern diffusion MRI sequences commonly acquire a large number of volumes with diffusion sensitization gradients of differing strengths or directions. Such sequences rely on echo-p…