63 citations · 99 across the 19 of their papers we have counts for
6 papers · 1 filter
Subject-specific quantitative susceptibility mapping using patch based deep image priors
Arvind Balachandrasekaran, Davood Karimi, Camilo Jaimes +1
Quantitative Susceptibility Mapping is a parametric imaging technique to estimate the magnetic susceptibilities of biological tissues from MRI phase measurements. This problem of e…
Atlas-powered deep learning (ADL) -- application to diffusion weighted MRI
Davood Karimi, Ali Gholipour
Deep learning has a great potential for estimating biomarkers in diffusion weighted magnetic resonance imaging (dMRI). Atlases, on the other hand, are a unique tool for modeling th…
Deep Learning Framework for Real-time Fetal Brain Segmentation in MRI
Razieh Faghihpirayesh, Davood Karimi, Deniz Erdogmus +1
Fetal brain segmentation is an important first step for slice-level motion correction and slice-to-volume reconstruction in fetal MRI. Fast and accurate segmentation of the fetal b…
Fetal Brain Tissue Annotation and Segmentation Challenge Results
Kelly Payette, Hongwei Li, Priscille de Dumast +55
In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital ste…
Learning to segment fetal brain tissue from noisy annotations
Davood Karimi, Caitlin K. Rollins, Clemente Velasco-Annis +2
Automatic fetal brain tissue segmentation can enhance the quantitative assessment of brain development at this critical stage. Deep learning methods represent the state of the art…
Diffusion Tensor Estimation with Transformer Neural Networks
Davood Karimi, Ali Gholipour
Diffusion tensor imaging (DTI) is a widely used method for studying brain white matter development and degeneration. However, standard DTI estimation methods depend on a large numb…