5 citations · 7 across the 5 of their papers we have counts for
14 papers
SuperWarp: Supervised Learning and Warping on U-Net for Invariant Subvoxel-Precise Registration
Sean I. Young, Yaël Balbastre, Adrian V. Dalca +3
In recent years, learning-based image registration methods have gradually moved away from direct supervision with target warps to instead use self-supervision, with excellent resul…
Unsupervised learning of MRI tissue properties using MRI physics models
Divya Varadarajan, Katherine L. Bouman, Andre van der Kouwe +2
In neuroimaging, MRI tissue properties characterize underlying neurobiology, provide quantitative biomarkers for neurological disease detection and analysis, and can be used to syn…
HyperMorph: Amortized Hyperparameter Learning for Image Registration
Andrew Hoopes, Malte Hoffmann, Bruce Fischl +2
We present HyperMorph, a learning-based strategy for deformable image registration that removes the need to tune important registration hyperparameters during training. Classical r…
Joint super-resolution and synthesis of 1 mm isotropic MP-RAGE volumes from clinical MRI exams with scans of different orientation, resolution and contrast
Juan Eugenio Iglesias, Benjamin Billot, Yael Balbastre +6
Most existing algorithms for automatic 3D morphometry of human brain MRI scans are designed for data with near-isotropic voxels at approximately 1 mm resolution, and frequently hav…
3D Reconstruction and Segmentation of Dissection Photographs for MRI-free Neuropathology
Henry Tregidgo, Adria Casamitjana, Caitlin Latimer +9
Neuroimaging to neuropathology correlation (NTNC) promises to enable the transfer of microscopic signatures of pathology to in vivo imaging with MRI, ultimately enhancing clinical…
Cortical surface registration using unsupervised learning
Jieyu Cheng, Adrian V. Dalca, Bruce Fischl +1
Non-rigid cortical registration is an important and challenging task due to the geometric complexity of the human cortex and the high degree of inter-subject variability. A convent…