Article

Clinical Implementation of Deep Learning MR reconstruction for TSE Sequences: Reduction of Acquisition Time and Maintenance

2021-02-03

Abstract excerpt

<h4>Background: </h4> The application of Deep Learning (DL) in MR image reconstruction is increasingly gaining attention due to its potential of increasing image quality and reducing acquisition time. However, the technology hasn’t been yet implemented in clinical routine. The aim of this study was therefore to describe the implementation of this novel DL image reconstruction for turbo spin echo (TSE) sequences in...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: dc72953c-91bd-5c11-bc54-c15bbb6535a5
DOI: 10.21203/rs.3.rs-153369/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Clinical Implementation of Deep Learning MR reconstruction for TSE Sequences: Reduction of Acquisition Time and MaintenanceDOI 10.21203/rs.3.rs-153369/v1Read

Comparison of image quality between Deep learning image reconstruction and Iterative reconstruction technique for CT Brain- a pilot studySemantic proximity Read

Deep Learning Initialized Compressed Sensing (Deli-CS) in Volumetric Spatio-Temporal Subspace ReconstructionSemantic proximity Read

Few-shot learning for highly accelerated 3D time-of-flight MRA reconstructionSemantic proximity Read

DL-based Highly-Accelerated Hepatobiliary-Phase Gadoxetate-Enhanced MRI ; Preliminary ExperienceSemantic proximity Read

Evaluating Second-Generation Deep Learning Technique for Noise Reduction in Myocardial T1-Mapping Magnetic Resonance ImagingSemantic proximity Read

Clinical utility of a rapid two-dimensional balanced steady-state free precession sequence with deep learning reconstructionSemantic proximity Read

Deep-Learning-Based Accelerated and Noise-Suppressed Estimation (DANSE) of quantitative Gradient Recalled Echo (qGRE) MRI metrics associated with Human Brain Neuronal Structure and Hemodynamic PropertiesSemantic proximity Read

Resolution Enhancement for Compressed Sensing at 1.5T MRI through Deep Learning: Application to Quantitative Volume Measurement of Human Brain StructuresSemantic proximity Read

The Value of a Deep Learning Image Reconstruction Algorithm on Low Dose Triphasic-enhanced Renal CTSemantic proximity Read

From 3D Time-of-Flight Angiography to Accelerated 4D Arterial Spin Labeling Angiography: A Fast Few-Shot Transfer Learning ApproachSemantic proximity Read

Can a Deep Progressive Learning Method Help to Achieve High Image Quality as Total-body PET Imaging?Semantic proximity Read

Monalisa: an open source, documented MATLAB toolbox for magnetic resonance imaging reconstructionSemantic proximity Read