Deep learning enables 60% accelerated volumetric brain MRI while preserving quantitative performance: a prospective, multicenter, multireader trial
BACKGROUND AND PURPOSE: In this prospective, multicenter, multireader study, we
evaluated the impact on both image quality and quantitative image-analysis consistency of …
evaluated the impact on both image quality and quantitative image-analysis consistency of …
[HTML][HTML] Applying deep learning to accelerated clinical brain magnetic resonance imaging for multiple sclerosis
Background: Magnetic resonance (MR) scans are routine clinical procedures for monitoring
people with multiple sclerosis (PwMS). Patient discomfort, timely scheduling, and financial …
people with multiple sclerosis (PwMS). Patient discomfort, timely scheduling, and financial …
Exploring the acceleration limits of deep learning variational network–based two-dimensional brain MRI
A Radmanesh, MJ Muckley, T Murrell… - Radiology: Artificial …, 2022 - pubs.rsna.org
Purpose To explore the limits of deep learning–based brain MRI reconstruction and identify
useful acceleration ranges for general-purpose imaging and potential screening. Materials …
useful acceleration ranges for general-purpose imaging and potential screening. Materials …
[HTML][HTML] The reliability of a deep learning model in clinical out-of-distribution MRI data: a multicohort study
Deep learning (DL) methods have in recent years yielded impressive results in medical
imaging, with the potential to function as clinical aid to radiologists. However, DL models in …
imaging, with the potential to function as clinical aid to radiologists. However, DL models in …
[HTML][HTML] Deep learning image processing enables 40% faster spinal MR scans which match or exceed quality of standard of care: a prospective multicenter …
Objective This prospective multicenter multireader study evaluated the performance of 40%
scan-time reduced spinal magnetic resonance imaging (MRI) reconstructed with deep …
scan-time reduced spinal magnetic resonance imaging (MRI) reconstructed with deep …
[HTML][HTML] Effect of MRI acquisition acceleration via compressed sensing and parallel imaging on brain volumetry
M Dieckmeyer, AG Roy, J Senapati… - … Resonance Materials in …, 2021 - Springer
Objectives To investigate the effect of compressed SENSE (CS), an acceleration technique
combining parallel imaging and compressed sensing, on potential bias and precision of …
combining parallel imaging and compressed sensing, on potential bias and precision of …
[HTML][HTML] Deep learning in large and multi-site structural brain MR imaging datasets
Large, multi-site, heterogeneous brain imaging datasets are increasingly required for the
training, validation and testing of advanced deep learning (DL)-based automated tools …
training, validation and testing of advanced deep learning (DL)-based automated tools …
A deep learning–based approach to reduce rescan and recall rates in clinical MRI examinations
A Sreekumari, D Shanbhag, D Yeo… - American Journal …, 2019 - Am Soc Neuroradiology
BACKGROUND AND PURPOSE: MR imaging rescans and recalls can create large hospital
revenue loss. The purpose of this study was to develop a fast, automated method for …
revenue loss. The purpose of this study was to develop a fast, automated method for …
Enhanced deep-learning-based magnetic resonance image reconstruction by leveraging prior subject-specific brain imaging: Proof-of-concept using a cohort of …
Deep learning models have shown potential for reconstructing undersampled, multi-channel
magnetic resonance (MR) image acquisitions. Recently proposed methods, however, have …
magnetic resonance (MR) image acquisitions. Recently proposed methods, however, have …
[HTML][HTML] Deep-learning-based reconstruction of undersampled MRI to reduce scan times: a multicentre, retrospective, cohort study
A Rastogi, G Brugnara, M Foltyn-Dumitru… - The Lancet …, 2024 - thelancet.com
Background The extended acquisition times required for MRI limit its availability in resource-
constrained settings. Consequently, accelerating MRI by undersampling k-space data …
constrained settings. Consequently, accelerating MRI by undersampling k-space data …