Related papers: A Self-Decoupled 32 Channel Receive Array for Huma…
Transmitter arrays play a critical role in ultra high field Magnetic Resonance Imaging (MRI), especially given the advantages made possible via parallel transmission (pTx) techniques. One of the challenges in design and construction of…
Purpose The goal of this work is to develop and evaluate a single-layer tight-fit 32-element double-tuned loop/dipole transceiver (TxRx) array for human brain 31P MRS at 9.4T, achieving reasonable transmit and receive performance and…
It is well known that magnetic resonance imaging (MRI) at 7 Tesla (7T) and higher magnets can provide much better signal sensitivity compared with lower field strengths. However, variety of commercially available ultra-high-field MRI coils…
Purpose: To evaluate an algorithm for calibrationless parallel imaging to reconstruct undersampled parallel transmit field maps for the body and brain. Methods: Using synthetic data, body, and brain measurements of relative transmit maps,…
Electromagnetic decoupling among a close-fitting or high-density transceiver RF array elements is required to maintain the integrity of the magnetic flux density from individual channel for enhanced performance in detection sensitivity and…
Modern magnetic resonance imaging (MRI) relies on application-specific multi-channel receive coils to achieve high performance, but these coils are typically costly, rigid, and difficult to generalize across anatomies. Recent wireless,…
Objective: Concurrent excitation and acquisition in MRI is a method to acquire MRI signal from tissues with very short transverse relaxation time. Since transmit power is many orders of magnitude larger than receive signal, a weak coupling…
In contrast to linearly polarized RF coil arrays, quadrature transceiver coil arrays are capable of improving signal-to-noise ratio (SNR), spatial resolution and parallel imaging performance. Owing to a reduced excitation power, low…
Ultra-high field MRI (7T+) unlocks a new era of brain research with superior resolution and signal-to-noise. Capturing intricate neural activity and detailed soft tissue pathology, this technology, coupled with advanced RF coil arrays,…
Novel methods and technology drive the rapid advances of nuclear magnetic resonance (NMR). The primary objective of developing novel hardware is to improve sensitivity and reliability (and possibly to reduce cost). Automation has made NMR…
Magnetic Resonance Imaging (MRI) acquisitions require extensive scan times, limiting patient throughput and increasing susceptibility to motion artifacts. Accelerated parallel MRI techniques reduce acquisition time by undersampling k-space…
The signal-to-noise ratio (SNR) in magnetic resonance imaging (MRI) governs the quality of signal detection and directly impacts the clarity and reliability of the acquired images. Recent advances in metamaterials have enabled lightweight…
Parallel imaging techniques have been widely used in high-field magnetic resonance imaging (MRI). Multiple receiver coils have been shown to improve image quality and allow accelerated image acquisition. Magnetic resonance imaging at…
In this work, we propose a novel energy-efficient spiking neural network (SNN)-based receiver for 5G-NR OFDM system, called neuromorphic receiver (NeuromorphicRx), replacing the channel estimation, equalization and symbol demapping blocks.…
We develop a novel next generation light-weight highly flexible pediatric coil array, combine it with a high-density pediatric posterior array or conventional posterior phased array, and determine feasibility of pediatric clinical use. A…
Diffusion MRI (dMRI) is a valuable imaging technique to study the brain in vivo. However, the resolution of dMRI is limited by the low signal-to-noise ratio (SNR) of this technique. Various acquisition strategies have been developed to…
While machine learning (ML)-based receiver algorithms have received a great deal of attention in the recent literature, they often suffer from poor scaling with increasing spatial multiplexing order and lack of explainability and…
Convolutional neural receivers such as DeepRx outperform minimum mean-square error physical uplink shared channel detection on in distribution channel and waveform configurations, but their behavior under calibration drift when transmitter…
Purpose: This study demonstrated an MR signal multitask learning method for 3D simultaneous segmentation and relaxometry of human brain tissues. Materials and Methods: A 3D inversion-prepared balanced steady-state free precession sequence…
To develop and evaluate a new deep learning MR denoising method that leverages quantitative noise distribution information from the reconstruction process to improve denoising performance and generalization. This retrospective study trained…