Diffusion models for medical image reconstruction

G Webber, AJ Reader - BJR| Artificial Intelligence, 2024 - academic.oup.com
Better algorithms for medical image reconstruction can improve image quality and enable
reductions in acquisition time and radiation dose. A prior understanding of the distribution of …

[HTML][HTML] Fast MRI Reconstruction Using Deep Learning-based Compressed Sensing: A Systematic Review

M Safari, Z Eidex, CW Chang, RLJ Qiu, X Yang - ArXiv, 2024 - ncbi.nlm.nih.gov
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 …

Unsupervised MRI motion artifact disentanglement: introducing MAUDGAN

M Safari, X Yang, CW Chang, RLJ Qiu… - Physics in Medicine …, 2024 - iopscience.iop.org
Objective. This study developed an unsupervised motion artifact reduction method for
magnetic resonance imaging (MRI) images of patients with brain tumors. The proposed …

Deep‐learning‐based motion correction using multichannel MRI data: a study using simulated artifacts in the fastMRI dataset

M Hewlett, I Petrov, PM Johnson… - NMR in …, 2024 - Wiley Online Library
Deep learning presents a generalizable solution for motion correction requiring no pulse
sequence modifications or additional hardware, but previous networks have all been …

[HTML][HTML] Deep learning-based prediction of later 13N-ammonia myocardial PET image frames from initial frames

M Mokri, M Safari, S Kaviani, D Juneau… - … Signal Processing and …, 2025 - Elsevier
Abstract Dynamic Myocardial Positron Emission Tomography (PET) evaluates myocardial
uptake. However, extended acquisition time during the dynamic PET can be a drawback …

A cardiac MRI motion artifact reduction method based on edge enhancement network

N Jiang, Y Zhang, Q Li, X Fu… - Physics in Medicine & …, 2024 - iopscience.iop.org
Cardiac magnetic resonance imaging (MRI) usually requires a long acquisition time. The
movement of the patients during MRI acquisition will produce image artifacts. Previous …

Adaptive Self-Supervised Consistency-Guided Diffusion Model for Accelerated MRI Reconstruction

M Safari, Z Eidex, S Pan, RLJ Qiu, X Yang - arXiv preprint arXiv …, 2024 - arxiv.org
Purpose: To propose a self-supervised deep learning-based compressed sensing MRI (DL-
based CS-MRI) method named" Adaptive Self-Supervised Consistency Guided Diffusion …

MRI data consistency guided conditional diffusion probabilistic model for MR imaging acceleration

M Safari, X Yang, A Fatemi - Medical Imaging 2024: Clinical …, 2024 - spiedigitallibrary.org
The long acquisition time required for high-resolution Magnetic Resonance Imaging (MRI)
leads to patient discomfort, increased likelihood of voluntary and involuntary movements …