Radio Frequency Image Research Articles

Linear Bloch-Siegert phase-encoded low-field MRI: RF coils, pulse sequence, and image reconstruction.

Conventional gradient systems have several weaknesses including high cost and bulk. As a step towards addressing these while providing new degrees of freedom for spatial encoding and system design in Magnetic Resonance Imaging (MRI), a radio frequency (RF) gradient encoding system and pulse sequence for phase encoding using the Bloch-Siegert (BS) shift were developed. Optimized BS spatial encoding coils with bucking windings (counter-wound loops) were designed and constructed, along with compatible homogeneous imaging coils for excitation and signal reception. Two coil systems were developed: one for phantom imaging and a second for human wrist imaging. BS phase-encoded imaging and BS RF pulse simulations were performed. Pulse sequences were designed for linear stepping in k-space and implemented on a 47.5-mT scanner to image resolution phantoms in both coil setups. Reconstructions were performed using both the full -based encoding fields for each BS pulse amplitude and using inverse discrete Fourier transforms. A gradient was used for frequency encoding during signal readout, and the third axis was projected. Specific absorption ratio (SAR) calculations were performed for the wrist coil to determine the safety of BS-based RF encoding for fields in the low field MRI regime. The optimized RF spatial encoding coils resulted in higher linearity ( and 0.9921 in the phantom and wrist coils, respectively) than coils used in previous work. The phantom and wrist imaging coils were validated in simulations and experimentally to produce a peak G and 0.8 G with 12-W input power, respectively, in the field-of-view (length = 11 cm) used for imaging. Nominal imaging resolutions of 5.22 and 7.21 mm were, respectively, achieved by the two-coil systems in the RF phase-encoded dimension. Coil systems, pulse sequences, and image reconstructions were developed for linear RF phase encoding using the BS shift and validated using a 47.5-mT open low field scanner, establishing a key component required for gradient-free imaging at low field strengths.

Photonic-Assisted Reconfigurable LO Harmonic Downconverter With RF Self-Interference Cancellation and Image-Rejection

A photonic-assisted reconfigurable LO harmonic downconverter with simultaneous image-rejection and RF self-interference cancellation (SIC) for in-band full-duplex communication is proposed and experimentally investigated based on a dual-polarization dual-parallel Mach–Zehnder modulator (DP-DPMZM). The received signal from the antenna, which includes the radio frequency (RF) signal, image signal (IM) and self-interference (SI) signal, is input into one sub-MZM of the X-DPMZM. The self-reference (SR) signal is input into the other. The Y-DPMZM is used to load the LO signal and is properly biased to obtain the high-order sideband of the LO signal, which was then set as the LO signal of the reconfigurable harmonic frequency downconverter. By matching the power and delay of the SR signal and changing the main bias of the X-DPMZM, the SI signal can be eliminated directly in optical domain. With power splitting after the output of the DP-DPMZM, the quadrature IF signals can be obtained by a photonics-based continuously adjustable phase shifter. Then, photonics image-rejection down-conversion based on phase cancellation is realized after a low-frequency electrical 90° hybrid coupler (HC) combines the quadrature IF signals. Both theoretical and experimental investigations are performed. The results show that the SIC has a cancellation depth more than 32 dB for the 10-MHz bandwidth and greater than 19 dB for the 500-MHz bandwidth, the image-rejection has an image-rejection ratio larger than 31 dB for 10-MHz bandwidth and larger than 22 dB for the 100-MHz bandwidth, both in 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nd</sup> - and 3 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rd</sup> -order harmonic down-conversion mode. Experiments are also carried out on the reconfigurable LO harmonic downconverter with simultaneous SIC and image-rejection. A 16-quadrature amplitude modulation (16-QAM) -modulated RF signal is successfully down-converted to a 1-GHz intermediate frequency (IF) signal with self-interference and image frequency cancelled. It is verified that the RF signal can be well recovered from SI and IM signals by the proposed system.

Stimulated Brillouin Scattering Based Image-Reject Microwave Signal Harmonic Down-Converter

We propose and demonstrate a photonic microwave signal harmonic down-converter with image rejection capability via stimulated Brillouin scattering (SBS). A dual-polarization dual-parallel Mach–Zehnder modulator (DP-DPMZM) is driven by a radio frequency/image (RF/IM) signal and a local oscillation (LO) signal to realize equivalent phase modulation and 4th-order double sideband modulation respectively. The optical carriers from the two arms of the DP-DPMZM can cancel out each other after polarization combining, thereby increasing the useful optical signal power in photodetection. Since the beating notes between the IM-modulated signals and LO-modulated 4th-order sidebands interfere destructively, the down-converted IM signals disappear naturally, which makes the down-converted image parts be suppressed in optical domain. By using an SBS-based dual-band microwave photonic filter to suppress the RF modulated -1st-order sideband and amplify the +1st-order sideband, destructive interference can be broken. Therefore, the RF signal over frequency range of 21-28 GHz can be down-converted to intermediate frequency (IF) band, and the image rejection ratio (IRR) can be also improved to more than 55 dB. Under -160 dBm/Hz noise floor, the SFDR is 105.1 dB·Hz <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2/3</sup> .

Validation of an RF Image System for Real-Time Tracking Neurosurgical Tools.

A radio frequency (RF)-based system for surgical navigation is presented. Surgical navigation technologies are widely used nowadays for aiding the surgical team with many interventions. However, the currently available options still pose considerable limitations, such as line-of-sight occlusion prevention or restricted materials and equipment allowance. In this work, we suggest a different approach based on a microwave broadband antenna system. We combine techniques from microwave medical imaging, which can overcome the current limitations in surgical navigation technologies, and we propose methods to develop RF-based systems for real-time tracking neurosurgical tools. The design of the RF system to perform the measurements is shown and discussed, and two methods (Multiply and Sum and Delay Multiply and Sum) for building the medical images are analyzed. From these measurements, a surgical tool’s position tracking system is developed and experimentally assessed in an emulated surgical scenario. The reported results are coherent with other approaches found in the literature, while overcoming their main practical limitations. The discussion of the results discloses some hints on the validity of the system, the optimal configurations depending on the requirements, and the possibilities for future enhancements.

High-resolution and high-contrast ultrafast ultrasound imaging using coherent plane wave adaptive compounding

Plane-wave imaging (PWI) is an interesting technique for increasing frame rate in medical ultrasound imaging, but it suffers from poor image quality. To overcome this problem, the coherent plane-wave compounding (CPWC) approach has been introduced, which provides the possibility of achieving the desired resolution and contrast by combining images obtained from different angles. In this paper, we proposed a new technique based on adaptive compounding of resulted radio frequency (RF) image data at different angles to obtain a high-resolution image. We called this method coherent plane wave adaptive compounding (CPWAC). The adaptive method used here is the minimum variance (MV) approach. An important benefit of the CPWAC method is that the calculation and inversion of the covariance matrix is done only once. We applied the proposed method on simulated, experimental, and in vivo datasets of the plane wave imaging challenge in medical ultrasound (PICMUS) data by considering 75 and 25 plane waves (PW). The results showed that the proposed CPWAC improves the lateral full width at half maximum (FWHM) by 35% for both simulated and experimental datasets, even by using 33% of the total angles compared to CPWC, which indicates simultaneous improvement of lateral resolution and frame rate. In addition, for the experimental dataset, this method has improved the {CR, CNR} about {103.8%, 100%} and {30.28%, 28%} in the near-field and far-field, respectively. Therefore, while the proposed method does not add much time overhead compared to the original CPWC, it improves the image quality of the CPWC significantly.

RODNet: A Real-Time Radar Object Detection Network Cross-Supervised by Camera-Radar Fused Object 3D Localization

Various autonomous or assisted driving strategies have been facilitated through the accurate and reliable perception of the environment around a vehicle. Among the commonly used sensors, radar has usually been considered as a robust and cost-effective solution even in adverse driving scenarios, e.g., weak/strong lighting or bad weather. Instead of considering to fuse the unreliable information from all available sensors, perception from pure radar data becomes a valuable alternative that is worth exploring. In this paper, we propose a deep radar object detection network, named RODNet, which is cross-supervised by a camera-radar fused algorithm without laborious annotation efforts, to effectively detect objects from the radio frequency (RF) images in real-time. First, the raw signals captured by millimeter-wave radars are transformed to RF images in range-azimuth coordinates. Second, our proposed RODNet takes a sequence of RF images as the input to predict the likelihood of objects in the radar field of view (FoV). Two customized modules are also added to handle multi-chirp information and object relative motion. Instead of using human-labeled ground truth for training, the proposed RODNet is cross-supervised by a novel 3D localization of detected objects using a camera-radar fusion (CRF) strategy in the training stage. Finally, we propose a method to evaluate the object detection performance of the RODNet. Due to no existing public dataset available for our task, we create a new dataset, named CRUW, which contains synchronized RGB and RF image sequences in various driving scenarios. With intensive experiments, our proposed cross-supervised RODNet achieves 86% average precision and 88% average recall of object detection performance, which shows the robustness to noisy scenarios in various driving conditions.

Improving the performance of a Malaysian pharmaceutical warehouse supply chain by integrating value stream mapping and discrete event simulation

Purpose Lean implementation is vastly incorporated in core manufacturing processes; however, its applicability in the supply chain and service industry is still in its infancy. To acquire performance excellence and thrive in the global competitive market, many firms are adopting newer methodologies. But, there is a stringent need for production simulation systems to analyze supply chains both inbound and outbound. The era of face validation is slowly disappearing. Lean tools and procedures that provide future state assumptions need advanced tools and techniques to measure, quantify, analyze and validate them. The purpose of this study is to enable dynamic quantification and visualization of the future state of a warehouse supply chain value stream map using discrete event simulation (DES) technique. Design/methodology/approach This study aimed to apply an integrated approach of the value stream mapping (VSM) and DES in a Malaysian pharmaceutical production warehouse. The main focus is diverted towards reducing the warehouse supply chain lead time by initially constructing a supply chain value stream map (both present state and future state) and integrating its data in a DES modelling and simulation software to dynamically visualize the changes in future state value stream map. Findings The DES simulation was able to mimic the future state lead time reductions successfully, which assists in better decision-making. Improvements were seen related to total lead time, process time, value and non-value-added percentage. Warehouse performance metrics such as receiving, put away and storage rates were substantially improved along with pallet processing time, worker and forklift throughput usage percentage. Detailed findings are clearly stated at the end of this paper. Research limitations/implications This study is limited to the warehouse environment and further additional process models and functional upgrades in the DES software systems are very much needed to directly visualize and quantify all the possible Lean assumptions such as radio frequency image identification/Andon (Jidoka), 5S, Kanban, Just-In-Time and Heijunka. However, DES has a leading edge in extracting dynamic characteristics out of a static VSM timeline and capture details on discrete events precisely by picturizing facility modification and lead time related to it. Practical implications This paper includes all the fundamental pharmaceutical warehouse supply chain processes and the simulations of the future state VSM in a real-life context by successfully reducing supply chain lead time and allowing managers in inculcating near-optimal decision-making, controlling and coordinating warehouse supply chain activities as a whole. Social implications This integrated approach of DES and VSM can involve managers and top management to support the adoption of anticipated changes. This study also has the potential to engage practitioners, researchers and decision-makers in the warehouse industry. Originality/value This study involves a powerful DES software package that can mimic the real situation as a virtual simulation and all the data and model building are based on a real warehouse scenario in the pharmaceutical industry.

Temporal Super-resolution of Ultrasound Imaging Using Matrix Completion.

The temporal super-resolution of the dynamic ultrasound imaging, a means to observe rapid heart movements, is considered an important subject in medical diagnosis of cardiac conditions. Here, a new technique based on the acquisition scheme using the matrix completion (MC) theory is offered for the temporal super-resolution of the two-dimensional (2D) and three-dimensional (3D) ultrasound imaging. MC mentions the problem of completing a low-rank matrix when only a subset of its elements can be observed. Here, the lower scan lines are acquired. Whereby, the proposed method uses temporal and spatial information of the radio frequency (RF) image sequences for the reconstruction of skipped RF lines. This is performed using the construction of the MC images and then reconstruction of them by the MC theory. The results of the proposed method are compared with the compressive sensing (CS) reconstruction methods. The qualitative and quantitative evaluations of 2D and 3D data demonstrate that in the proposed method, which uses the spatial and temporal relation of RF images and the MC theory, the reconstruction is more accurate, and the reconstruction error is lower. The computational complexity of this method is very low. It also does not require hardware adjustments. Therefore, it can be easily implemented in current ultrasound-imaging devices with the frame-rate enhancement. For instance, the frame rate up to two times the original sequence is feasible using the proposed methods, while root mean square error is decreased by about 35% and 30% for 2D and 3D data, respectively, compared with the CS reconstruction method.

Three-dimensional image integration guidance for cryoballoon pulmonary vein isolation procedures.

We present a new, easily applicable approach for the guidance of cryoballoon (CB) pulmonary vein isolation (PVI) procedures that use the combination of a 3D-mapping system image integration module and computed tomographic (CT)-derived anatomy. The aim of this retrospective, nonrandomized study was to investigate: (a) an alternative use for an established radiofrequency image integration module for cryo procedures; (b) a guidance technology for cryo PVI based on integrated CT anatomy; and (c) its clinical impact. CT left atrium-angiography was performed in 50 consecutive patients before a CB PVI procedure, and a 3D reconstruction of the cardiac anatomy was segmented. A total of 25 patients were treated using conventional fluoroscopy; 25 patients were treated using the 3D image integration technique. In the image integration group, the CARTO3 UNIVU (Biosense Webster) module was used for image integration of 3D anatomy and fluoroscopic imaging. Transseptal puncture and cryo PVI were guided by 3D-overlay imaging. Procedures were feasible without complications in all patients and cryo PVI procedures were successfully guided using the image integration technique. The intraprocedural time needed to perform image integration was 37 ± 10 seconds. Fluoroscopy time was 31.7 ± 11.7 minutes in the conventional group and 20.1 ± 7.9 minutes in the image integration group (P < .001), procedure time was 116.3 ± 29.0 minutes in the conventional group vs 101.2 ± 20.9 minutes in the 3D group (P = .04). 3D-overlay guidance of CB PVI is feasible, safe, and applicable in real time with minimal effort. It may significantly reduce radiation exposure by introducing 3D information, known from electroanatomic mapping systems, into cryo PVI procedures.

Kalman-Filter Accelerated k-Space Tomography

A Kalman filter is applied to the k-space tomography imaging modality for state-space prediction of radio frequency (RF) sources. By seeding the Kaczmarz computed tomography algorithm with Kalman filtered predictions, spatial-spectral reconstruction of the RF environment is accelerated. This technique enables an N/M decrease in reconstruction time, where M is the standard number of iterations required to fully reconstruct the RF image and N is the number of iterations required when the algorithm is seeded with a correct Kalman filter input.

Spatial Angular Compounding Technique for H-Scan Ultrasound Imaging

H-Scan is a new ultrasound imaging technique that relies on matching a model of pulse-echo formation to the mathematics of a class of Gaussian-weighted Hermite polynomials. This technique may be beneficial in the measurement of relative scatterer sizes and in cancer therapy, particularly for early response to drug treatment. Because current H-scan techniques use focused ultrasound data acquisitions, spatial resolution degrades away from the focal region and inherently affects relative scatterer size estimation. Although the resolution of ultrasound plane wave imaging can be inferior to that of traditional focused ultrasound approaches, the former exhibits a homogeneous spatial resolution throughout the image plane. The purpose of this study was to implement H-scan using plane wave imaging and investigate the impact of spatial angular compounding on H-scan image quality. Parallel convolution filters using two different Gaussian-weighted Hermite polynomials that describe ultrasound scattering events are applied to the radiofrequency data. The H-scan processing is done on each radiofrequency image plane before averaging to get the angular compounded image. The relative strength from each convolution is color-coded to represent relative scatterer size. Given results from a series of phantom materials, H-scan imaging with spatial angular compounding more accurately reflects the true scatterer size caused by reductions in the system point spread function and improved signal-to-noise ratio. Preliminary in vivo H-scan imaging of tumor-bearing animals suggests this modality may be useful for monitoring early response to chemotherapeutic treatment. Overall, H-scan imaging using ultrasound plane waves and spatial angular compounding is a promising approach for visualizing the relative size and distribution of acoustic scattering sources.

Underwater radio frequency image sensor using progressive image compression and region of interest

The increasing demand for underwater robotic intervention systems around the world in several application domains requires more versatile and inexpensive systems. By using a wireless communication system, supervised semi-autonomous robots have freedom of movement; however, the limited and varying bandwidth of underwater radio frequency (RF) channels is a major obstacle for the operator to get camera feedback and supervise the intervention. This paper proposes the use of progressive (embedded) image compression and region of interest (ROI) for the design of an underwater image sensor to be installed in an autonomous underwater vehicle, specially when there are constraints on the available bandwidth, allowing a more agile data exchange between the vehicle and a human operator supervising the underwater intervention. The operator can dynamically decide the size, quality, frame rate, or resolution of the received images so that the available bandwidth is utilized to its fullest potential and with the required minimum latency. The paper focuses first on the description of the system, which uses a camera, an embedded Linux system, and an RF emitter installed in an OpenROV housing cylinder. The RF receiver is connected to a computer on the user side, which controls the camera monitoring parameters, including the compression inputs, such as region of interest (ROI), size of the image, and frame rate. The paper focuses on the compression subsystem and does not attempt to improve the communications physical media for better underwater RF links. Instead, it proposes a unified system that uses well-integrated modules (compression and transmission) to provide the scientific community with a higher-level protocol for image compression and transmission in sub-sea robotic interventions.

Securing clinic tele-diagnostic system using enhanced tiny encrypted radio frequency identification and image steganographic technique

Traditional health record systems are gradually giving way for automated solutions capable of delivery robust e-healthcare systems. Existing models of e-healthcare system carries with it challenges of privacy breach in electronic health record (EHR) authentication system. The existence of patients' private data within the channel of communication could be intercepted, interpreted and used fraudulently leading to loss of data confidentiality. Also, an unprotected RFID tag in EHR system could be cloned and impersonated thus, depriving the patients of guaranteed privacy. In this paper, we present a crystographic approach for securing data communications in clinic tele-diagnostic system (CTDS). Analysis of the performance of the system showed an imperceptible stego image with peak signal to noise ratio greater than 30 db. Furthermore, valid patient's RFID tag was authenticated with the developed pseudo-random tiny encryption-based RFID-EHR system. The performance evaluation of the system portrays a system capable of counteracting the effects of tag cloning, location tracking and replay attacks in data communication channels of clinic tele-consultations.

Securing clinic tele-diagnostic system using enhanced tiny encrypted radio frequency identification and image steganographic technique

Traditional health record systems are gradually giving way for automated solutions capable of delivery robust e-healthcare systems. Existing models of e-healthcare system carries with it challenges of privacy breach in electronic health record (EHR) authentication system. The existence of patients' private data within the channel of communication could be intercepted, interpreted and used fraudulently leading to loss of data confidentiality. Also, an unprotected RFID tag in EHR system could be cloned and impersonated thus, depriving the patients of guaranteed privacy. In this paper, we present a crystographic approach for securing data communications in clinic tele-diagnostic system (CTDS). Analysis of the performance of the system showed an imperceptible stego image with peak signal to noise ratio greater than 30 db. Furthermore, valid patient's RFID tag was authenticated with the developed pseudo-random tiny encryption-based RFID-EHR system. The performance evaluation of the system portrays a system capable of counteracting the effects of tag cloning, location tracking and replay attacks in data communication channels of clinic tele-consultations.

Experimental Measurement System for 3-6 GHz Microwave Breast Tomography

This paper presents an experimental measurement system for 3?6 GHz microwave tomography (MT) of the breast. The measurement system is constructed as a minimal test bed to verify key components such as the sensing antennas, radio frequency (RF) transceiver, sensing mechanism, and image reconstruction method for our advanced MT system detecting breast cancer at an early stage. The test bed has eight RF channels operating at 3 to 6 GHz for high spatial resolution and a two-axis scanning mechanism for three-dimensional measurement. The measurement results from the test bed are shown and discussed.

Fast multistation water/fat imaging at 3T using DREAM-based RF shimming.

To show the effect, efficiency, and image quality improvements achievable by Dual Refocusing Echo Acquisition Mode (DREAM)-based B1+ shimming in whole-body magnetic resonance imaging (MRI) at 3T using the example of water/fat imaging. 3D multistation, dual-echo mDixon gradient echo imaging was performed in 10 healthy subjects on a clinical 3T dual-transmit MRI system using station-to-station adapted B1+ shimming based on fast DREAM B1+ mapping. Whole-body data were obtained using conventional quadrature excitation and station-by-station adapted DREAM-based B1+ shimmed excitation, along with the corresponding B1+ maps for both excitation modes to assess image quality and radiofrequency (RF) performance. Station-dependent DREAM-based B1+ shimming showed significantly improved image quality in the stations covering the upper legs, pelvis, and upper body region for all subjects (P < 0.02). This finding is supported by corresponding B1+ maps showing an improved B1+ homogeneity and a more precise flip angle in the DREAM-based B1+ shimmed excitation (P < 0.01). Furthermore, the very short dual-channel DREAM B1+ mapping times of less than 2 seconds facilitate quick B1+ shimming. Station-dependent DREAM-based B1+ shimming improved RF performance and image quality and is therefore a promising technique for whole-body multistation imaging applications.

High-frame-rate 2-D vector blood flow imaging in the frequency domain.

Conventional ultrasound Doppler techniques estimate the blood velocity exclusively in the axial direction to produce the sonograms and color flow maps needed for diagnosis of cardiovascular diseases. In this paper, a novel method to produce bi-dimensional maps of 2-D velocity vectors is proposed. The region of interest (ROI) is illuminated by plane waves transmitted at the pulse repetition frequency (PRF) in a fixed direction. For each transmitted plane wave, the backscattered echoes are recombined offline to produce the radio-frequency image of the ROI. The local 2-D phase shifts between consecutive speckle images are efficiently estimated in the frequency domain, to produce vector maps up to 15 kHz PRF. Simulations and in vitro steady-flow experiments with different setup conditions have been conducted to thoroughly evaluate the method's performance. Bias is proved to be lower than 10% in most simulations and lower than 20% in experiments. Further simulations and in vivo experiments have been made to test the approach's feasibility in pulsatile flow conditions. It has been estimated that the computation of the frequency domain algorithm is more than 50 times faster than the computation of the reference 2-D cross-correlation algorithm.

Nonlinear ultrasound simulation for heterogeneous nonlinear coefficient media

In medical ultrasound, the use of simulation tools is very common to develop and test new imaging strategies. The existing tools are mainly limited to the linear propagation of ultrasound waves in tissue. A specific difficulty is due to the fact that the nonlinearity of investigated media can be different at different depths and the local value of the nonlinear coefficient must be taken into account to provide realistic simulated images. CREANUIS is a new two-step tool to simulate ultrasound images of linear and nonlinear media. It is based on a generalized angular spectrum method to consider the nonlinear forward propagation with heterogeneous nonlinear map and uses a reconstruction algorithm to create the corresponding radio frequency image. The simulated linear images have been validated through the comparison with images provided by FieldII, the reference tool in linear ultrasound simulation. CREANUIS allows simulating various nonlinear imaging techniques such as amplitude modulation or pulse inversion. Examples of images obtained simulating tissues with heterogeneous coefficients of nonlinearity will be presented. The comparison with experimental images provided by the ULA-OP ultrasound system and a grayscale phantom highlight the performance of CREANUIS images. CREANUIS is freely available at http://www.creatis.insa-lyon.fr/site/fr/CREANUIS.

Research on the Design of Intelligent Access Control System Based on Radio Frequency Technology and Image Processing Technology

With the continually development of computer technology and modern communication technology, radio frequency technology and image processing technology become the important component of modern security system. In particular, the application of the intelligent access control system of the two technologies becomes a hot research topic in the field. This article first briefly analyzes the principle of radio frequency technology and establishes intelligent access control system based on radio frequency technology and image processing technology. It analyzes the theory and application compatibility of this system which provides technical support and theoretical basic for the researches in this field to some extent.

Impact of 3.0 T Cardiac MR Imaging Using Dual-Source Parallel Radiofrequency Transmission with Patient-Adaptive B1 Shimming

ObjectivesTo prospectively evaluate the impact of 3.0 T Cardiac MR imaging using dual-source parallel radiofrequency (RF) transmission with patient-adaptive B1 shimming compared with single-source RF transmission in the RF homogeneity, image contrast and image quality.MethodsThe study was approved by the local institutional review board, and all subjects provided written informed consent. Fourteen healthy volunteers were examined at 3.0 T MR, with both the conventional single-source and the new dual-source RF transmission. B1 calibrations (RF shimming) of the heart region were performed to acquire a percent of the prescribed flip angle (FA) of B1 maps, which were used for quantitative assessment of RF homogeneity. Contrast ratios (CRs) between ventricular blood pool and septum were calculated on balanced-turbo field echo (B-TFE) cine images. The off-resonance artifacts of cine images were blindly assessed by two radiologists according to a 4-point grading-scale.ResultsA significantly lower mean coefficients of variance of the achieved FA with dual-source revealed better RF homogeneity compared to single-source (P = 0.0094). Dual-source RF shimming significantly increased the CRs (P<0.05) and reduced the off-resonance artifacts of B-TFE cine images (P<0.05). Inter-observer agreement for the off-resonance artifacts of B-TFE cine images was good to excellent (k >0.65).ConclusionsDual-source parallel RF transmission significantly improves the RF homogeneity, increases image contrast and reduces image artifacts of cardiac B-TFE images compared to single-source mode. This may be of value in reducing the observer-dependence of cardiac MR images and enhancing diagnostic confidence for clinical practice using CMR at 3.0 T.