4 citations · 8 across the 8 of their papers we have counts for
8 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…
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…
Automatic Segmentation of the Prostate on 3D Trans-rectal Ultrasound Images using Statistical Shape Models and Convolutional Neural Networks
Golnoosh Samei, Davood Karimi, Claudia Kesch +1
In this work we propose to segment the prostate on a challenging dataset of trans-rectal ultrasound (TRUS) images using convolutional neural networks (CNNs) and statistical shape m…
Interpolation of CT Projections by Exploiting Their Self-Similarity and Smoothness
Davood Karimi, Rabab K. Ward
As the medical usage of computed tomography (CT) continues to grow, the radiation dose should remain at a low level to reduce the health risks. Therefore, there is an increasing ne…
A machine learning-based method for estimating the number and orientations of major fascicles in diffusion-weighted magnetic resonance imaging
Davood Karimi, Lana Vasung, Camilo Jaimes +4
Multi-compartment modeling of diffusion-weighted magnetic resonance imaging measurements is necessary for accurate brain connectivity analysis. Existing methods for estimating the…
Sparse and redundant signal representations for x-ray computed tomography
Davood Karimi
Image models are central to all image processing tasks. The great advancements in digital image processing would not have been made possible without powerful models which, themselv…