A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction

The acquisition of Magnetic Resonance Imaging (MRI) is inherently slow. Inspired by recent advances in deep learning, we propose a framework for reconstructing MR images from undersampled data using a deep cascade of convolutional neural networks to accelerate the data acquisition process. We show that for Cartesian undersampling of 2D cardiac MR images, the proposed method outperforms the state-of-the-art compressed sensing approaches, such as dictionary learning-based MRI (DLMRI) reconstruction, in terms of reconstruction error, perceptual quality and reconstruction speed for both 3-fold and 6-fold undersampling. Compared to DLMRI, the error produced by the method proposed is approximately twice as small, allowing to preserve anatomical structures more faithfully. Using our method, each image can be reconstructed in 23 ms, which is fast enough to enable real-time applications

APIR-Net: Autocalibrated Parallel Imaging Reconstruction using a Neural Network

Deep learning has been successfully demonstrated in MRI reconstruction of accelerated acquisitions. However, its dependence on representative training data limits the application across different contrasts, anatomies, or image sizes. To address this limitation, we propose an unsupervised, auto-calibrated k-space completion method, based on a uniquely designed neural network that reconstructs the full k-space from an undersampled k-space, exploiting the redundancy among the multiple channels in the receive coil in a parallel imaging acquisition. To achieve this, contrary to common convolutional network approaches, the proposed network has a decreasing number of feature maps of constant size. In contrast to conventional parallel imaging methods such as GRAPPA that estimate the prediction kernel from the fully sampled autocalibration signals in a linear way, our method is able to learn nonlinear relations between sampled and unsampled positions in k-space. The proposed method was compared to the start-of-the-art ESPIRiT and RAKI methods in terms of noise amplification and visual image quality in both phantom and in-vivo experiments. The experiments indicate that APIR-Net provides a promising alternative to the conventional parallel imaging methods, and results in improved image quality especially for low SNR acquisitions.Comment: To appear in the proceedings of MICCAI 2019 Workshop Machine Learning for Medical Image Reconstructio

MRI of the lung (1/3):methods

Proton magnetic resonance imaging (MRI) has recently emerged as a clinical tool to image the lungs. This paper outlines the current technical aspects of MRI pulse sequences, radiofrequency (RF) coils and MRI system requirements needed for imaging the pulmonary parenchyma and vasculature. Lung MRI techniques are presented as a “technical toolkit”, from which MR protocols will be composed in the subsequent papers for comprehensive imaging of lung disease and function (parts 2 and 3). This paper is pitched at MR scientists, technicians and radiologists who are interested in understanding and establishing lung MRI methods. Images from a 1.5 T scanner are used for illustration of the sequences and methods that are highlighted. Main Messages • Outline of the hardware and pulse sequence requirements for proton lung MRI • Overview of pulse sequences for lung parenchyma, vascular and functional imaging with protons • Demonstration of the pulse-sequence building blocks for clinical lung MRI protocol

Three dimensional three component whole heart cardiovascular magnetic resonance velocity mapping: comparison of flow measurements from 3D and 2D acquisitions

<p>Abstract</p> <p>Background</p> <p>Two-dimensional, unidirectionally encoded, cardiovascular magnetic resonance (CMR) velocity mapping is an established technique for the quantification of blood flow in large vessels. However, it requires an operator to correctly align the planes of acquisition. If all three directional components of velocity are measured for each voxel of a 3D volume through the phases of the cardiac cycle, blood flow through any chosen plane can potentially be calculated retrospectively. The initial acquisition is then more time consuming but relatively operator independent.</p> <p>Aims</p> <p>To compare the curves and volumes of flow derived from conventional 2D and comprehensive 3D flow acquisitions in a steady state flow model, and in vivo through planes transecting the ascending aorta and pulmonary trunk in 10 healthy volunteers.</p> <p>Methods</p> <p>Using a 1.5 T Phillips Intera CMR system, 3D acquisitions used an anisotropic 3D segmented k-space phase contrast gradient echo sequence with a short EPI readout, with prospective ECG and diaphragm navigator gating. The 2D acquisitions used segmented k-space phase contrast with prospective ECG and diaphragm navigator gating. Quantitative flow analyses were performed retrospectively with dedicated software for both the in vivo and in vitro acquisitions.</p> <p>Results</p> <p>Analysis of in vitro data found the 3D technique to have overestimated the continuous flow rate by approximately 5% across the entire applied flow range. In vivo, the 2D and the 3D techniques yielded similar volumetric flow curves and measurements. Aortic flow: (mean ± SD), 2D = 89.5 ± 13.5 ml & 3D = 92.7 ± 17.5 ml. Pulmonary flow: 2D = 98.8 ± 18.4 ml & 3D = 94.9 ± 19.0 ml). Each in vivo 3D acquisition took about 8 minutes or more.</p> <p>Conclusion</p> <p>Flow measurements derived from the 3D and 2D acquisitions were comparable. Although time consuming, comprehensive 3D velocity acquisition could be relatively operator independent, and could potentially yield information on flow through several retrospectively chosen planes, for example in patients with congenital or valvular heart disease.</p

Fast spin echo sequences for BOLD functional MRI

At higher field strengths, spin echo (SE) functional MRI (fMRI) is an attractive alternative to gradient echo (GE) as the increased weighting towards the microvasculature results in intrinsically better localization of the BOLD signal. Images are free of signal voids but the commonly used echo planar imaging (EPI) sampling scheme causes geometric distortions, and T2* effects often contribute considerably to the signal changes measured upon brain activation. Multiply refocused SE sequences such as fast spin echo (FSE) are essentially artifact free but their application to fast fMRI is usually hindered due to high energy deposition, and long sampling times. In the work presented here, a combination of parallel imaging and partial Fourier acquisition is used to shorten FSE acquisition times to near those of conventional SE-EPI, permitting sampling of eight slices (matrix 64  ×  64) per second. Signal acquisition is preceded by a preparation experiment that aims at increasing the relative contribution of extravascular dynamic averaging to the BOLD signal. Comparisons are made with conventional SE-EPI using a visual stimulation paradigm. While the observed signal changes are approximately 30% lower, most likely due to the absence of T2* contamination, activation size and t-scores are comparable for both methods, suggesting that HASTE fMRI is a viable alternative, particularly if distortion free images are required. Our data also indicate that the BOLD post-stimulus undershoot is most probably attributable to persistent elevated oxygen metabolism rather than to delayed vascular compliance

Parallel imaging: is GRAPPA a useful acquisition tool for MR imaging intended for volumetric brain analysis?

<p>Abstract</p> <p>Background</p> <p>The work presented here investigates parallel imaging applied to T1-weighted high resolution imaging for use in longitudinal volumetric clinical studies involving Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) patients. This was in an effort to shorten acquisition times to minimise the risk of motion artefacts caused by patient discomfort and disorientation. The principle question is, "Can parallel imaging be used to acquire images at 1.5 T of sufficient quality to allow volumetric analysis of patient brains?"</p> <p>Methods</p> <p>Optimisation studies were performed on a young healthy volunteer and the selected protocol (including the use of two different parallel imaging acceleration factors) was then tested on a cohort of 15 elderly volunteers including MCI and AD patients. In addition to automatic brain segmentation, hippocampus volumes were manually outlined and measured in all patients. The 15 patients were scanned on a second occasion approximately one week later using the same protocol and evaluated in the same manner to test repeatability of measurement using images acquired with the GRAPPA parallel imaging technique applied to the MPRAGE sequence.</p> <p>Results</p> <p>Intraclass correlation tests show that almost perfect agreement between repeated measurements of both segmented brain parenchyma fraction and regional measurement of hippocampi. The protocol is suitable for both global and regional volumetric measurement dementia patients.</p> <p>Conclusion</p> <p>In summary, these results indicate that parallel imaging can be used without detrimental effect to brain tissue segmentation and volumetric measurement and should be considered for both clinical and research studies where longitudinal measurements of brain tissue volumes are of interest.</p

Current CONtrolled Transmit And Receive Coil Elements (C2ONTAR) for Parallel Acquisition and Parallel Excitation Techniques at High-Field MRI

A novel intrinsically decoupled transmit and receive radio-frequency coil element is presented for applications in parallel imaging and parallel excitation techniques in high-field magnetic resonance imaging. Decoupling is achieved by a twofold strategy: during transmission elements are driven by current sources, while during signal reception resonant elements are switched to a high input impedance preamplifier. To avoid B0 distortions by magnetic impurities or DC currents a resonant transmission line is used to relocate electronic components from the vicinity of the imaged object. The performance of a four-element array for 3 T magnetic resonance tomograph is analyzed by means of simulation, measurements of electromagnetic fields and bench experiments. The feasibility of parallel acquisition and parallel excitation is demonstrated and compared to that of a conventional power source-driven array of equivalent geometry. Due to their intrinsic decoupling the current-controlled elements are ideal basic building blocks for multi-element transmit and receive arrays of flexible geometry