4 papers · 1 filter
Self-Supervised Adversarial Diffusion Models for Fast MRI Reconstruction
Mojtaba Safari, Zach Eidex, Shaoyan Pan +2
Purpose: To propose a self-supervised deep learning-based compressed sensing MRI (DL-based CS-MRI) method named "Adaptive Self-Supervised Consistency Guided Diffusion Model (ASSCGD…
T1-contrast Enhanced MRI Generation from Multi-parametric MRI for Glioma Patients with Latent Tumor Conditioning
Zach Eidex, Mojtaba Safari, Richard L. J. Qiu +4
Objective: Gadolinium-based contrast agents (GBCAs) are commonly used in MRI scans of patients with gliomas to enhance brain tumor characterization using T1-weighted (T1W) MRI. How…
Deep Learning Based Apparent Diffusion Coefficient Map Generation from Multi-parametric MR Images for Patients with Diffuse Gliomas
Zach Eidex, Mojtaba Safari, Jacob Wynne +6
Purpose: Apparent diffusion coefficient (ADC) maps derived from diffusion weighted (DWI) MRI provides functional measurements about the water molecules in tissues. However, DWI is…
Fast MRI Reconstruction Using Deep Learning-based Compressed Sensing: A Systematic Review
Mojtaba Safari, Zach Eidex, Chih-Wei Chang +2
Magnetic resonance imaging (MRI) has revolutionized medical imaging, providing a non-invasive and highly detailed look into the human body. However, the long acquisition times of M…