research
∙
05/05/2023
Physics-based network fine-tuning for robust quantitative susceptibility mapping from high-pass filtered phase
Purpose: To improve the generalization ability of convolutional neural n...
share
research
∙
11/01/2022
LARO: Learned Acquisition and Reconstruction Optimization to accelerate Quantitative Susceptibility Mapping
Quantitative susceptibility mapping (QSM) involves acquisition and recon...
research
∙
05/04/2021
Motion Artifact Reduction in Quantitative Susceptibility Mapping using Deep Neural Network
An approach to reduce motion artifacts in Quantitative Susceptibility Ma...
research
∙
03/06/2021
NeRD: Neural Representation of Distribution for Medical Image Segmentation
We introduce Neural Representation of Distribution (NeRD) technique, a m...
research
∙
09/30/2020
DEEPMIR: A DEEP convolutional neural network for differential detection of cerebral Microbleeds and IRon deposits in MRI
Background: Cerebral microbleeds (CMBs) and non-hemorrhage iron deposits...
research
∙
09/29/2020
Geometric Loss for Deep Multiple Sclerosis lesion Segmentation
Multiple sclerosis (MS) lesions occupy a small fraction of the brain vol...
research
∙
09/13/2020
Efficient Folded Attention for 3D Medical Image Reconstruction and Segmentation
Recently, 3D medical image reconstruction (MIR) and segmentation (MIS) b...
research
∙
07/28/2020
Extending LOUPE for K-space Under-sampling Pattern Optimization in Multi-coil MRI
The previously established LOUPE (Learning-based Optimization of the Und...
research
∙
02/27/2020
