713 citations · 2.5k across the 20 of their papers we have counts for
9 papers · 1 filter
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…
Learning the Effect of Registration Hyperparameters with HyperMorph
Andrew Hoopes, Malte Hoffmann, Douglas N. Greve +3
We introduce HyperMorph, a framework that facilitates efficient hyperparameter tuning in learning-based deformable image registration. Classical registration algorithms perform an…
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…
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…
Fast Infant MRI Skullstripping with Multiview 2D Convolutional Neural Networks
Amod Jog, P. Ellen Grant, Joseph L. Jacobson +4
Skullstripping is defined as the task of segmenting brain tissue from a full head magnetic resonance image~(MRI). It is a critical component in neuroimage processing pipelines. Dow…
Unsupervised Deep Learning for Bayesian Brain MRI Segmentation
Adrian V. Dalca, Evan Yu, Polina Golland +3
Probabilistic atlas priors have been commonly used to derive adaptive and robust brain MRI segmentation algorithms. Widely-used neuroimage analysis pipelines rely heavily on these…
PSACNN: Pulse Sequence Adaptive Fast Whole Brain Segmentation
Amod Jog, Andrew Hoopes, Douglas N. Greve +2
With the advent of convolutional neural networks~(CNN), supervised learning methods are increasingly being used for whole brain segmentation. However, a large, manually annotated t…
Pulse Sequence Resilient Fast Brain Segmentation
Amod Jog, Bruce Fischl
Accurate automatic segmentation of brain anatomy from -weighted~(-w) magnetic resonance images~(MRI) has been a computationally intensive bottleneck in neuroimaging pipel…
Joint registration and synthesis using a probabilistic model for alignment of MRI and histological sections
Juan Eugenio Iglesias, Marc Modat, Loic Peter +6
Nonlinear registration of 2D histological sections with corresponding slices of MRI data is a critical step of 3D histology reconstruction. This task is difficult due to the large…