Emerging trends in fast MRI using deep-learning reconstruction on undersampled k-space data: a systematic review

D Singh, A Monga, HL de Moura, X Zhang, MVW Zibetti… - Bioengineering, 2023 - mdpi.com
Magnetic Resonance Imaging (MRI) is an essential medical imaging modality that provides
excellent soft-tissue contrast and high-resolution images of the human body, allowing us to …

A review of PET attenuation correction methods for PET-MR

G Krokos, J MacKewn, J Dunn, P Marsden - EJNMMI physics, 2023 - Springer
Despite being thirteen years since the installation of the first PET-MR system, the scanners
constitute a very small proportion of the total hybrid PET systems installed. This is in stark …

Convex optimization algorithms in medical image reconstruction—in the age of AI

J Xu, F Noo - Physics in Medicine & Biology, 2022 - iopscience.iop.org
The past decade has seen the rapid growth of model based image reconstruction (MBIR)
algorithms, which are often applications or adaptations of convex optimization algorithms …

Joint diffusion: mutual consistency-driven diffusion model for PET-MRI co-reconstruction

T Xie, ZX Cui, C Luo, H Wang, C Liu… - Physics in Medicine …, 2024 - iopscience.iop.org
Objective. Positron Emission Tomography and Magnetic Resonance Imaging (PET-MRI)
systems can obtain functional and anatomical scans. But PET suffers from a low signal-to …

Deep learning applications for quantitative and qualitative PET in PET/MR: technical and clinical unmet needs

J Yang, A Afaq, R Sibley, A McMilan… - … Resonance Materials in …, 2024 - Springer
We aim to provide an overview of technical and clinical unmet needs in deep learning (DL)
applications for quantitative and qualitative PET in PET/MR, with a focus on attenuation …

Accuracy and longitudinal consistency of PET/MR attenuation correction in amyloid PET imaging amid software and hardware upgrades

C Ying, Y Chen, Y Yan, S Flores, R Laforest… - American Journal of …, 2024 - ajnr.org
ABSTRACT BACKGROUND AND PURPOSE: Integrated PET/MR allows the simultaneous
acquisition of PET biomarkers and structural and functional MRI to study Alzheimer disease …

A study of Bayesian deep network uncertainty and its application to synthetic CT generation for MR‐only radiotherapy treatment planning

MWK Law, MY Tse, LCC Ho, KK Lau, OL Wong… - Medical …, 2024 - Wiley Online Library
Background The use of synthetic computed tomography (CT) for radiotherapy treatment
planning has received considerable attention because of the absence of ionizing radiation …

Physics-driven deep learning for pet/mri

A Rajagopal, AP Leynes, N Dwork, JE Scholey… - arXiv preprint arXiv …, 2022 - arxiv.org
In this paper, we review physics-and data-driven reconstruction techniques for simultaneous
positron emission tomography (PET)/magnetic resonance imaging (MRI) systems, which …

SoftDropConnect (SDC)--Effective and Efficient Quantification of the Network Uncertainty in Deep MR Image Analysis

Q Lyu, CT Whitlow, G Wang - arXiv preprint arXiv:2201.08418, 2022 - arxiv.org
Recently, deep learning has achieved remarkable successes in medical image analysis.
Although deep neural networks generate clinically important predictions, they have inherent …

Advanced Methods for Photon Attenuation and Scatter Correction for Combined Positron Emission Tomography and Magnetic Resonance Imaging (PET/MRI)

EA Anaya - 2023 - search.proquest.com
Combined positron emission tomography and magnetic resonance (PET/MR) imaging
combines the molecular information from PET with the structural information from MR, which …