Real-time MRI
View article: Deep Magnetic Resonance Image Reconstruction: Inverse Problems Meet Neural Networks
Deep Magnetic Resonance Image Reconstruction: Inverse Problems Meet Neural Networks Open
Image reconstruction from undersampled k-space data has been playing an important role in fast MRI. Recently, deep learning has demonstrated tremendous success in various fields and has also shown potential in significantly accelerating MR…
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Radiotherapy planning using MRI Open
The use of magnetic resonance imaging (MRI) in radiotherapy (RT) planning is rapidly expanding. We review the wide range of image contrast mechanisms available to MRI and the way they are exploited for RT planning. However a number of chal…
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Compressed sensing for body MRI Open
The introduction of compressed sensing for increasing imaging speed in magnetic resonance imaging (MRI) has raised significant interest among researchers and clinicians, and has initiated a large body of research across multiple clinical a…
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Applications of deep learning to MRI images: A survey Open
Deep learning provides exciting solutions in many fields, such as image analysis, natural language processing, and expert system, and is seen as a key method for various future applications. On account of its non-invasive and good soft tis…
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Plug-and-Play Methods for Magnetic Resonance Imaging: Using Denoisers for Image Recovery Open
Magnetic Resonance Imaging (MRI) is a non-invasive diagnostic tool that provides excellent soft-tissue contrast without the use of ionizing radiation. Compared to other clinical imaging modalities (e.g., CT or ultrasound), however, the dat…
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MRI-only treatment planning: benefits and challenges Open
Over the past decade, the application of magnetic resonance imaging (MRI) has increased, and there is growing evidence to suggest that improvements in the accuracy of target delineation in MRI-guided radiation therapy may improve clinical …
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A Fast Fractal Based Compression for MRI Images Open
Magnetic resonance imaging (MRI), which assists doctors in determining clinical staging and expected surgical range, has high medical value. A large number of MRI images require a large amount of storage space and the transmission bandwidt…
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Optimization Methods for Magnetic Resonance Image Reconstruction: Key Models and Optimization Algorithms Open
The development of compressed sensing methods for magnetic resonance (MR) image reconstruction led to an explosion of research on models and optimization algorithms for MR imaging (MRI). Roughly 10 years after such methods first appeared i…
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Three‐dimensional motion corrected sensitivity encoding reconstruction for multi‐shot multi‐slice MRI: Application to neonatal brain imaging Open
Purpose To introduce a methodology for the reconstruction of multi‐shot, multi‐slice magnetic resonance imaging able to cope with both within‐plane and through‐plane rigid motion and to describe its application in structural brain imaging.…
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Nuts and bolts of 4D-MRI for radiotherapy Open
Magnetic resonance imaging (MRI) is increasingly being used in the radiotherapy workflow because of its superior soft tissue contrast and high flexibility in contrast. In addition to anatomical and functional imaging, MRI can also be used …
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Magnetic resonance image (MRI) synthesis from brain computed tomography (CT) images based on deep learning methods for magnetic resonance (MR)-guided radiotherapy Open
Quantitative comparisons suggest that the performance of U-Net, a supervised deep learning method, is better than the performance of CycleGAN, a typical unsupervised method, in our brain MRI synthesis procedure. The proposed method can con…
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Recommendations for real-time speech MRI Open
Real-time magnetic resonance imaging (RT-MRI) is being increasingly used for speech and vocal production research studies. Several imaging protocols have emerged based on advances in RT-MRI acquisition, reconstruction, and audio-processing…
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Automated Segmentation of Brain Tumor MRI Images Using Deep Learning Open
Segmenting brain tumors automatically using MR data is crucial for disease investigation and monitoring. Due to the aggressive nature and diversity of gliomas, well-organized and exact segmentation methods are used to classify tumors intra…
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Development of a mobile low-field MRI scanner Open
Magnetic resonance imaging (MRI) allows important visualization of the brain and central nervous system anatomy and organization. However, unlike electroencephalography (EEG) or functional near infrared spectroscopy, which can be brought t…
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Protocols for multi‐site trials using hyperpolarized <sup>129</sup>Xe MRI for imaging of ventilation, alveolar‐airspace size, and gas exchange: A position paper from the <sup>129</sup>Xe MRI clinical trials consortium Open
Hyperpolarized (HP) 129 Xe MRI uniquely images pulmonary ventilation, gas exchange, and terminal airway morphology rapidly and safely, providing novel information not possible using conventional imaging modalities or pulmonary function tes…
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Direct Patlak Reconstruction From Dynamic PET Data Using the Kernel Method With MRI Information Based on Structural Similarity Open
Positron emission tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neuroscience. It is highly sensitive, but suffers from relatively poor spatial resolution, as compared with anatomical imaging mod…
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Mapping the human subcortical auditory system using histology, postmortem MRI and in vivo MRI at 7T Open
Studying the human subcortical auditory system non-invasively is challenging due to its small, densely packed structures deep within the brain. Additionally, the elaborate three-dimensional (3-D) structure of the system can be difficult to…
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Real‐Time Magnetic Resonance Imaging Open
Real‐time magnetic resonance imaging (RT‐MRI) allows for imaging dynamic processes as they occur, without relying on any repetition or synchronization. This is made possible by modern MRI technology such as fast‐switching gradients and par…
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Real-time magnetic resonance-guided ablation of typical right atrial flutter using a combination of active catheter tracking and passive catheter visualization in man: initial results from a consecutive patient series Open
The combination of active catheter tracking and passive real-time visualization in CMR-guided electrophysiologic (EP) studies using advanced interventional hardware and software was safe and enabled efficient navigation, mapping, and ablat…
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Motion prediction in MRI-guided radiotherapy based on interleaved orthogonal cine-MRI Open
In-room cine-MRI guidance can provide non-invasive target localization during radiotherapy treatment. However, in order to cope with finite imaging frequency and system latencies between target localization and dose delivery, tumour motion…
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Cine Cardiac MRI Motion Artifact Reduction Using a Recurrent Neural Network Open
Cine cardiac magnetic resonance imaging (MRI) is widely used for the diagnosis of cardiac diseases thanks to its ability to present cardiovascular features in excellent contrast. As compared to computed tomography (CT), MRI, however, requi…
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NeSVoR: Implicit Neural Representation for Slice-to-Volume Reconstruction in MRI Open
Reconstructing 3D MR volumes from multiple motion-corrupted stacks of 2D slices has shown promise in imaging of moving subjects, e. g., fetal MRI. However, existing slice-to-volume reconstruction methods are time-consuming, especially when…
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Fetal cardiac cine imaging using highly accelerated dynamic MRI with retrospective motion correction and outlier rejection Open
Purpose Development of a MRI acquisition and reconstruction strategy to depict fetal cardiac anatomy in the presence of maternal and fetal motion. Methods The proposed strategy involves i) acquisition and reconstruction of highly accelerat…
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Multi-Contrast Brain MRI Image Super-Resolution With Gradient-Guided Edge Enhancement Open
In magnetic resonance imaging (MRI), the super-resolution technology has played a great role in improving image quality. The aim of this paper is to improve edges of brain MRI by incorporating the gradient information of another contrast h…
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Music‐based magnetic resonance fingerprinting to improve patient comfort during MRI examinations Open
Purpose Unpleasant acoustic noise is a drawback of almost every MRI scan. Instead of reducing acoustic noise to improve patient comfort, we propose a technique for mitigating the noise problem by producing musical sounds directly from the …
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Advances in real-time phase-contrast flow MRI using asymmetric radial gradient echoes Open
Asymmetric gradient echoes were successfully implemented for highly undersampled radial trajectories. The resulting temporal gain offers full velocity compensation for real-time phase-contrast flow MRI which minimizes false-positive contri…
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PILOT: Physics-Informed Learned Optimized Trajectories for Accelerated MRI Open
Magnetic Resonance Imaging (MRI) has long been considered to be among “the gold standards” of diagnostic medical imaging. The long acquisition times, however, render MRI prone to motion artifacts, let alone their adverse contribution to th…
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PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI Open
In this paper, we present a novel method for the correction of motion artifacts that are present in fetal magnetic resonance imaging (MRI) scans of the whole uterus. Contrary to current slice-to-volume registration (SVR) methods, requiring…
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Time-Dependent Deep Image Prior for Dynamic MRI Open
We propose a novel unsupervised deep-learning-based algorithm for dynamic magnetic resonance imaging (MRI) reconstruction. Dynamic MRI requires rapid data acquisition for the study of moving organs such as the heart. Existing reconstructio…
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Fetal cardiac cine magnetic resonance imaging in utero Open
Fast magnetic resonance imaging (MRI) led to the emergence of ‘cine MRI’ techniques, which enable the visualization of the beating heart and the assessment of cardiac morphology and dynamics. However, established cine MRI methods are not s…