A fully programmable computing architecture for medical ultrasound machines

An FPGA-Accelerated Parallel Digital Beamforming Core for Medical Ultrasound Sector Imaging

Plane-wave transmission followed by parallel receive beamforming is popular among high frame rate (HFR) ultrasound (US) imaging methods. However, due to technological limitations, HFR imaging is not widely successful in clinical US. The proposed work aims to design a field-programmable gate array (FPGA)-accelerated parallel beamforming core for medical US sector imaging systems. This architecture supports up to 128 channels and forms 28 beams per plane wave transmission in parallel. A block random access memories (BRAMs)-based, 28-read one-write (28R1W) multi-ported delay line architecture is actualized to realize the delay line. In addition, to optimize the FPGA memory, the required beam focusing delays are stored in an external static random access memory (SRAM) and are loaded into the internal delay line registers by a cycle stealing direct memory access (DMA). The FPGA prototype validation and verification are performed on the custom-designed Xilinx-Kintex-7 XC7C410T FPGA-based US imaging platform. The results showed that for a field of view (FOV) of 90° with 0.5° resolution, 640×480 imaging size, a ft/s of 714 is achieved. The performance of the proposed parallel beamformer architecture is compared with existing development works and concluded that the architecture is superior due to its occupancy of FPGA hardware resources and the processing speed.

A 3-D Ultrasound Wearable Array Prognosis System With Advanced Imaging Capabilities

In the last few decades, the medical and healthcare scientific communities have focused their attention on the use or development of real-time monitoring devices and remote control systems. New generations of wearable, portable, and implantable devices offer better and more accurate measurements/prognosis for those that suffer from diseases and/or disabilities. Thus, there are still challenging issues of current ultrasound imaging (USI) systems, such as low-quality ultrasound images, slow time response to emergencies, and location-based operation. Thus, in response to these challenges, we present a new low-cost, portable/wearable 3-D array ultrasound prognosis system with advanced imaging capabilities that offer high-resolution (HR) accurate results in a near real-time response. The USI unique features are based on 2-D array transducers with 3-D overlapping capabilities and a new image enhancement methodology compatible with the system's structural characteristics to compensate for any loss of image quality. This system will offer an alternative way of ultrasound examination, independent of the radiologist's skills, that is, a system to be capable of automatic scanning of the volume of interest (VOI) without the guidance of the radiologist.

Towards A Pixel-Level Reconfigurable Digital Beamforming Core for Ultrasound Imaging

Ultrasound (US) imaging systems typically employ a single beamforming scheme which is the delay and sum (DAS) beamforming due to its reduced complexity. However, DAS results in images with limited resolution and contrast. The limitations of DAS have been overcome by, delay multiply and sum (DMAS) beamforming, making it especially preferable in cases where finer image details are required in larger depth of scans for an accurate diagnosis. But, DMAS is confined to transducer frequencies where the generated harmonics also fall in the processable frequency range of the US system. However, if US systems could provide the flexibility to reconfigure beamforming considering the restrictions of each beamforming scheme, it is possible to select the best beamforming according to the clinical requirement and system constraints. This work is a fundamental step towards enabling reconfigurable beamforming for on-the-fly selection among the DAS and DMAS beamforming schemes, with low reconfiguration overhead, specifically for each imaging scenario to aid better diagnosis. Two novel architectures are proposed, that reconfigures between DAS and DMAS beamforming as a function of transducer's center frequency with minimum additional computational overhead. The implementation results of the proposed architectures on xc7z010clg400-1 FPGA are reported. The possibilities of pixel-level beamforming reconfigurability, where the different tissue regions are beamformed with either DAS or DMAS are also shown through simulations.

Compact and Programmable Ultrasound Front-End Processing Module for Research Activities

Ultrasound signal processing involves diversified requirements in terms of processing, power, hardware etc. Ultrasound signal processing is continuously evolving area, and hence researchers who need to evaluate the novel algorithms in real time need to have the complete hardware setup. Commercially available ultrasound scanners are based on Application Specific Integrated Circuit (ASIC) and hence it does not have any provision to test the novel algorithms. In this paper, we propose a compact and programmable module, equipped with required hardware support for implementing complete front-end processing. The board is supported with an external interface that can be connected to other computing platforms like Field-Programmable Gate Arrays (FPGA's), and Digital Signal Processors (DSP's), etc, for implementing the mid-end and back-end algorithms. Provision is provided for acquiring the raw RF data, which will be beneficial for developing computer-aided diagnostics, and also to develop signal processing algorithms in offline. The proposed front-end hardware module will be very beneficial for rapid testing of the novel ultrasound signal processing algorithms.

Toward Optimal Computation of Ultrasound Image Reconstruction Using CPU and GPU

An ultrasound image is reconstructed from echo signals received by array elements of a transducer. The time of flight of the echo depends on the distance between the focus to the array elements. The received echo signals have to be delayed to make their wave fronts and phase coherent before summing the signals. In digital beamforming, the delays are not always located at the sampled points. Generally, the values of the delayed signals are estimated by the values of the nearest samples. This method is fast and easy, however inaccurate. There are other methods available for increasing the accuracy of the delayed signals and, consequently, the quality of the beamformed signals; for example, the in-phase (I)/quadrature (Q) interpolation, which is more time consuming but provides more accurate values than the nearest samples. This paper compares the signals after dynamic receive beamforming, in which the echo signals are delayed using two methods, the nearest sample method and the I/Q interpolation method. The comparisons of the visual qualities of the reconstructed images and the qualities of the beamformed signals are reported. Moreover, the computational speeds of these methods are also optimized by reorganizing the data processing flow and by applying the graphics processing unit (GPU). The use of single and double precision floating-point formats of the intermediate data is also considered. The speeds with and without these optimizations are also compared.

A System-on-Chip Solution for Point-of-Care Ultrasound Imaging Systems: Architecture and ASIC Implementation

In this paper, we present a novel system-on-chip (SOC) solution for a portable ultrasound imaging system (PUS) for point-of-care applications. The PUS-SOC includes all of the signal processing modules (i.e., the transmit and dynamic receive beamformer modules, mid- and back-end processors, and color Doppler processors) as well as an efficient architecture for hardware-based imaging methods (e.g., dynamic delay calculation, multi-beamforming, and coded excitation and compression). The PUS-SOC was fabricated using a UMC 130-nm NAND process and has 16.8 GFLOPS of computing power with a total equivalent gate count of 12.1 million, which is comparable to a Pentium-4 CPU. The size and power consumption of the PUS-SOC are 27×27 mm(2) and 1.2 W, respectively. Based on the PUS-SOC, a prototype hand-held US imaging system was implemented. Phantom experiments demonstrated that the PUS-SOC can provide appropriate image quality for point-of-care applications with a compact PDA size ( 200×120×45 mm(3)) and 3 hours of battery life.

Transform-Based Channel-Data Compression to Improve the Performance of a Real-Time GPU-Based Software Beamformer

Graphics processing unit (GPU)-based software beamforming has advantages over hardware-based beamforming of easier programmability and a faster design cycle, since complicated imaging algorithms can be efficiently programmed and modified. However, the need for a high data rate when transferring ultrasound radio-frequency (RF) data from the hardware front end to the software back end limits the real-time performance. Data compression methods can be applied to the hardware front end to mitigate the data transfer issue. Nevertheless, most decompression processes cannot be performed efficiently on a GPU, thus becoming another bottleneck of the real-time imaging. Moreover, lossless (or nearly lossless) compression is desirable to avoid image quality degradation. In a previous study, we proposed a real-time lossless compression-decompression algorithm and demonstrated that it can reduce the overall processing time because the reduction in data transfer time is greater than the computation time required for compression/decompression. This paper analyzes the lossless compression method in order to understand the factors limiting the compression efficiency. Based on the analytical results, a nearly lossless compression is proposed to further enhance the compression efficiency. The proposed method comprises a transformation coding method involving modified lossless compression that aims at suppressing amplitude data. The simulation results indicate that the compression ratio (CR) of the proposed approach can be enhanced from nearly 1.8 to 2.5, thus allowing a higher data acquisition rate at the front end. The spatial and contrast resolutions with and without compression were almost identical, and the process of decompressing the data of a single frame on a GPU took only several milliseconds. Moreover, the proposed method has been implemented in a 64-channel system that we built in-house to demonstrate the feasibility of the proposed algorithm in a real system. It was found that channel data from a 64-channel system can be transferred using the standard USB 3.0 interface in most practical imaging applications.

Ultrasound in Radiology: From Anatomic, Functional, Molecular Imaging to Drug Delivery and Image-Guided Therapy

During the past decade, ultrasound has expanded medical imaging well beyond the "traditional" radiology setting: a combination of portability, low cost, and ease of use makes ultrasound imaging an indispensable tool for radiologists as well as for other medical professionals who need to obtain imaging diagnosis or guide a therapeutic intervention quickly and efficiently. Ultrasound combines excellent ability for deep penetration into soft tissues with very good spatial resolution, with only a few exceptions (ie, those involving overlying bone or gas). Real-time imaging (up to hundreds and thousands of frames per second) enables guidance of therapeutic procedures and biopsies; characterization of the mechanical properties of the tissues greatly aids with the accuracy of the procedures. The ability of ultrasound to deposit energy locally brings about the potential for localized intervention encompassing the following: tissue ablation, enhancing penetration through the natural barriers to drug delivery in the body and triggering drug release from carrier microparticles and nanoparticles. The use of microbubble contrast agents brings the ability to monitor and quantify tissue perfusion, and microbubble targeting with ligand-decorated microbubbles brings the ability to obtain molecular biomarker information, that is, ultrasound molecular imaging. Overall, ultrasound has become the most widely used imaging modality in modern medicine; it will continue to grow and expand.

Lossless data compression for improving the performance of a GPU-based beamformer

The powerful parallel computation ability of a graphics processing unit (GPU) makes it feasible to perform dynamic receive beamforming However, a real time GPU-based beamformer requires high data rate to transfer radio-frequency (RF) data from hardware to software memory, as well as from central processing unit (CPU) to GPU memory. There are data compression methods (e.g. Joint Photographic Experts Group (JPEG)) available for the hardware front end to reduce data size, alleviating the data transfer requirement of the hardware interface. Nevertheless, the required decoding time may even be larger than the transmission time of its original data, in turn degrading the overall performance of the GPU-based beamformer. This article proposes and implements a lossless compression-decompression algorithm, which enables in parallel compression and decompression of data. By this means, the data transfer requirement of hardware interface and the transmission time of CPU to GPU data transfers are reduced, without sacrificing image quality. In simulation results, the compression ratio reached around 1.7. The encoder design of our lossless compression approach requires low hardware resources and reasonable latency in a field programmable gate array. In addition, the transmission time of transferring data from CPU to GPU with the parallel decoding process improved by threefold, as compared with transferring original uncompressed data. These results show that our proposed lossless compression plus parallel decoder approach not only mitigate the transmission bandwidth requirement to transfer data from hardware front end to software system but also reduce the transmission time for CPU to GPU data transfer.

Elastography using multi-stream GPU: an application to online tracked ultrasound elastography, in-vivo and the da Vinci Surgical System

A system for real-time ultrasound (US) elastography will advance interventions for the diagnosis and treatment of cancer by advancing methods such as thermal monitoring of tissue ablation. A multi-stream graphics processing unit (GPU) based accelerated normalized cross-correlation (NCC) elastography, with a maximum frame rate of 78 frames per second, is presented in this paper. A study of NCC window size is undertaken to determine the effect on frame rate and the quality of output elastography images. This paper also presents a novel system for Online Tracked Ultrasound Elastography (O-TRuE), which extends prior work on an offline method. By tracking the US probe with an electromagnetic (EM) tracker, the system selects in-plane radio frequency (RF) data frames for generating high quality elastograms. A novel method for evaluating the quality of an elastography output stream is presented, suggesting that O-TRuE generates more stable elastograms than generated by untracked, free-hand palpation. Since EM tracking cannot be used in all systems, an integration of real-time elastography and the da Vinci Surgical System is presented and evaluated for elastography stream quality based on our metric. The da Vinci surgical robot is outfitted with a laparoscopic US probe, and palpation motions are autonomously generated by customized software. It is found that a stable output stream can be achieved, which is affected by both the frequency and amplitude of palpation. The GPU framework is validated using data from in-vivo pig liver ablation; the generated elastography images identify the ablated region, outlined more clearly than in the corresponding B-mode US images.

An FPGA-based ultrasound imaging system using capacitive micromachined ultrasonic transducers

We report the design and experimental results of a field-programmable gate array (FPGA)-based real-time ultrasound imaging system that uses a 16-element phased-array capacitive micromachined ultrasonic transducer fabricated using a fusion bonding process. The imaging system consists of the transducer, discrete analog components situated on a custom-made circuit board, the FPGA, and a monitor. The FPGA program consists of five functional blocks: a main counter, transmit and receive beamformer, receive signal pre-processing, envelope detection, and display. No dedicated digital signal processor or personal computer is required for the imaging system. An experiment is carried out to obtain the sector B-scan of a 4-wire target. The ultrasound imaging system demonstrates the possibility of an integrated system-in-a-package solution.

A single FPGA-based portable ultrasound imaging system for point-of-care applications

We present a cost-effective portable ultrasound system based on a single field-programmable gate array (FPGA) for point-of-care applications. In the portable ultrasound system developed, all the ultrasound signal and image processing modules, including an effective 32-channel receive beamformer with pseudo-dynamic focusing, are embedded in an FPGA chip. For overall system control, a mobile processor running Linux at 667 MHz is used. The scan-converted ultrasound image data from the FPGA are directly transferred to the system controller via external direct memory access without a video processing unit. The potable ultrasound system developed can provide real-time B-mode imaging with a maximum frame rate of 30, and it has a battery life of approximately 1.5 h. These results indicate that the single FPGA-based portable ultrasound system developed is able to meet the processing requirements in medical ultrasound imaging while providing improved flexibility for adapting to emerging POC applications.

Compounded direct pixel beamforming for medical ultrasound imaging

In this paper, a new compounded direct pixel beamforming (CDPB) method is presented to remove blurring artifacts introduced by ultrasound scan conversion. In CDPB, receive focusing is directly performed on each display pixel in Cartesian coordinates using the raw RF data from adjacent transmit firings so that artifacts from the scan conversion can be removed. In addition, the energy variations resulting from the distance between the transmit scanline and display pixel are compensated by utilizing the gain factor obtained from the ultrasound beam pattern. The proposed CDPB method was evaluated using simulation and in vivo liver data acquired by a commercial ultrasound machine equipped with a research package. The experimental results showed that the proposed CDPB method improved the information entropy contrast (IEC) by 23.6% compared with the conventional scan conversion method and it reduced the blocking artifacts factor (BAF) by 16.4% over the direct pixel-based focusing method. These results indicate the proposed new direct pixel beamforming method could be used to enhance image quality in medical ultrasound imaging.

Reconstruction algorithm for improved ultrasound image quality

A new algorithm is proposed for reconstructing raw RF data into ultrasound images. Previous delay-and-sum beamforming reconstruction algorithms are essentially one-dimensional, because a sum is performed across all receiving elements. In contrast, the present approach is two-dimensional, potentially allowing any time point from any receiving element to contribute to any pixel location. Computer-intensive matrix inversions are performed once, in advance, to create a reconstruction matrix that can be reused indefinitely for a given probe and imaging geometry. Individual images are generated through a single matrix multiplication with the raw RF data, without any need for separate envelope detection or gridding steps. Raw RF data sets were acquired using a commercially available digital ultrasound engine for three imaging geometries: a 64-element array with a rectangular field-of- view (FOV), the same probe with a sector-shaped FOV, and a 128-element array with rectangular FOV. The acquired data were reconstructed using our proposed method and a delay- and-sum beamforming algorithm for comparison purposes. Point spread function (PSF) measurements from metal wires in a water bath showed that the proposed method was able to reduce the size of the PSF and its spatial integral by about 20 to 38%. Images from a commercially available quality-assurance phantom had greater spatial resolution and contrast when reconstructed with the proposed approach.