High frame rate velocity-coded speckle imaging platform for coherent blood flow visualization

Session 2aBA - Biomedical Acoustics: Biomedical Ultrasound Imaging Instrumentation: no. 2aBA1 (Invited Paper)Non-invasive imaging of blood flow at over 100 fps (i.e. beyond video display range) is known to be of clinical interest given that such a high frame rate is essential for coherent visualization of complex hemodynamic events like flow turbulence. From a technical standpoint, getting into this frame rate range has became possible with the advent of broad-view ultrasound imaging paradigms that can track motion over an entire field-of-view using few pulse-echo firings. Leveraging on an imaging paradigm known as plane wave excitation, a novel high-frame-rate flow visualization technique has been developed to depict both blood speckle motion (using B-flow imaging principles) and flow velocities (using conventional color flow imaging principles). Experimental demonstration of this method has been carried out using a channel-domain research platform that supports real-time pre-beamformed data acquisition (SonixDAQ) and a high-throughput processing engine that is based upon graphical processing unit technology (developed in-house by the authors). In a case with a 417 fps frame rate (based on 5000 Hz pulse repetition frequency and slow-time ensemble size of 12), results show that high-frame-rate velocity-coded speckle imaging can more coherently trace fast-moving blood flow than conventional color flow imaging. Acknowledgement: Research Grants Council of Hong Kong (GRF 785811M)published_or_final_versio

Real-time GPU-based software beamformer designed for advanced imagingmethods research

High computational demand is known to be a technical hurdle for real-timeimplementation of advanced methods like synthetic aperture imaging (SAI) andplane wave imaging (PWI) that work with the pre-beamform data of each arrayelement. In this paper, we present the development of a software beamformer forSAI and PWI with real-time parallel processing capacity. Our beamformer designcomprises a pipelined group of graphics processing units (GPU) that are hostedwithin the same computer workstation. During operation, each available GPU isassigned to perform demodulation and beamforming for one frame of pre-beamformdata acquired from one transmit firing (e.g. point firing for SAI). Tofacilitate parallel computation, the GPUs have been programmed to treat thecalculation of depth pixels from the same image scanline as a block ofprocessing threads that can be executed concurrently, and it would repeat thisprocess for all scanlines to obtain the entire frame of image data i.e.low-resolution image (LRI). To reduce processing latency due to repeated accessof each GPU's global memory, we have made use of each thread block's fast-sharedmemory (to store an entire line of pre-beamform data during demodulation),created texture memory pointers, and utilized global memory caches (to streamrepeatedly used data samples during beamforming). Based on this beamformerarchitecture, a prototype platform has been implemented for SAI and PWI, and itsLRI processing throughput has been measured for test datasets with 40 MHzsampling rate, 32 receive channels, and imaging depths between 5-15 cm. Whenusing two Fermi-class GPUs (GTX-470), our beamformer can compute LRIs of512-by-255 pixels at over 3200 fps and 1300 fps respectively for imaging depthsof 5 cm and 15 cm. This processing throughput is roughly 3.2 times higher than aTesla-class GPU (GTX-275). © 2010 IEEE.published_or_final_versionThe 2010 IEEE International Ultrasonics Symposium, San Diego, CA., 11-14 October 2010. In Proceedings of IEEE IUS, 2010, p. 1920-192

A fast parallelized eigen-based clutter filter framework for ultrasound color flow imaging

Oral presentation - IUS1-D3: Novel imaging systems: abstract no. IUS1-D3-6The Conference program & abstracts' website is located at http://www.ewh.ieee.org/conf/uffc/2013/BACKGROUND, MOTIVATION AND OBJECTIVE: Eigen-filters with attenuation response adapted to clutter statistics have emerged as a new class of clutter suppression techniques in color flow imaging (CFI) to achieve high flow detection sensitivity in the presence of tissue motion. There is growing interest to extend this technique beyond laboratory investigations by incorporating it into the CFI processing routine on ultrasound scanners. Nevertheless, bridging such a gap from theory to practice is known to be challenging from a real-time computing perspective because the singular value decomposition (SVD) operation in eigen-filtering is known to pose heavy computational burden. Here we seek to overcome this issue by formulating a new technical framework that enables fast execution of eigen-filtering so as to foster their practical adoption in …postprin

GPU-based beamformer: Fast realization of plane wave compounding and synthetic aperture imaging

Although they show potential to improve ultrasound image quality, plane wave (PW) compounding and synthetic aperture (SA) imaging are computationally demanding and are known to be challenging to implement in real-time. In this work, we have developed a novel beamformer architecture with the real-time parallel processing capacity needed to enable fast realization of PW compounding and SA imaging. The beamformer hardware comprises an array of graphics processing units (GPUs) that are hosted within the same computer workstation. Their parallel computational resources are controlled by a pixel-based software processor that includes the operations of analytic signal conversion, delay-and-sum beamforming, and recursive compounding as required to generate images from the channel-domain data samples acquired using PW compounding and SA imaging principles. When using two GTX-480 GPUs for beamforming and one GTX-470 GPU for recursive compounding, the beamformer can compute compounded 512 × 255 pixel PW and SA images at throughputs of over 4700 fps and 3000 fps, respectively, for imaging depths of 5 cm and 15 cm (32 receive channels, 40 MHz sampling rate). Its processing capacity can be further increased if additional GPUs or more advanced models of GPU are used. © 2011 IEEE.published_or_final_versio

High frame rate vector flow imaging of stenotic carotid bifurcation: computational modeling and analysis

Poster Session Session P1Aa. Beam Formation: Computational Aspects And Artifact Reduction: no. P1Ab-1Analysis of the complex blood flow pattern in the carotid bifurcation is clinically important to the diagnosis of carotid stenoses. We hypothesize that the use of high frame rate imaging methods such as plane wave excitation, together with vector flow estimators like block matching, may potentially be a suitable imaging problem to this problem. This paper presents our team’s initial efforts in developing a high frame rate vector flow imaging framework that is based on plane wave excitation principles and a high dynamic range block matching algorithm that incorporates least squares fitting principles. We have conducted a series of Field II simulations on straight tubes and carotid bifurcation to evaluate the estimation accuracy and imaging performance of our framework. Results indicate that high-frame-rate vector flow imaging is capable of visualizing complex blood flow. It has potential to be further developed into a new clinical technique for vascular diagnoses.published_or_final_versionThe 2011 IEEE International Ultrasonics Symposium (IUS), Orlando, FL., 18-21 October 2011. In IEEE International Ultrasonics Symposium Proceedings, 2011, p. 409-41

Anthropomorphic flow phantom design using stereolithography: a novel approach based on direct fabrication of thin-walled compliant vessels

The Conference program & abstracts' website is located at http://www.ewh.ieee.org/conf/uffc/2013/Session IUS1-PC2: Blood velocity estimation and applications: abstract no. IUS1-PC2-3BACKGROUND, MOTIVATION AND OBJECTIVE: Anatomically realistic flow phantoms are essential tools for vascular ultrasound investigations. They are conventionally developed using investment casting; however, this technique is known to require skilled craftsmanship, and it is difficult to incorporate multiple pathological features into the phantom’s vessel geometry. In this work, we seek to devise a new phantom design framework that can efficiently produce complex vessel models resembling diseased arteries. Stereolithography is proposed here as a direct way of fabricating thin-walled compliant vessels …postprin

Medical ultrasound imaging: To GPU or not to GPU?

Medical ultrasound imaging stands out from other modalities in providing real-time diagnostic capability at an affordable price while being physically portable. This article explores the suitability of using GPUs as the primary signal and image processors for future medical ultrasound imaging systems. A case study on synthetic aperture (SA) imaging illustrates the promise of using high-performance GPUs in such systems. © 2011 IEEE.published_or_final_versio

High-frame-rate color-encoded speckle imaging for visually intuitive rendering of complex flow dynamics

Oral presentation - IUS1-B2: 3D and vector velocity imaging: abstract no. US1-B2-6The Conference program & abstracts' website is located at http://www.ewh.ieee.org/conf/uffc/2013/BACKGROUND, MOTIVATION AND OBJECTIVE: Realization of flow imaging at high frame rates can undoubtedly benefit the visualization of complex flow patterns with significant spatiotemporal variations. It would be even better if fluid motion can be coherently rendered through parallel display of both flow trajectory and flow speed. Driven by these motivations, we have developed a new high-frame-rate ultrasound flow visualization technique called color-encoded speckle imaging (CESI). It provides a visually intuitive interpretation of complex flow through a hybrid display format that shows both flow speckle pattern and color-encoded velocity mapping. STATEMENT OF CONTRIBUTION/METHODS: CESI works by integrating two key principles: 1) using broad-view data acquisition schemes …postprin

Real-time GPU-based adaptive beamformer for high quality ultrasound imaging

Poster Session Session P1Aa. Beam Formation: Computational Aspects And Artifact Reduction: no. P1Ac-7A real-time adaptive minimum variance (MV) beam-former realized using graphics processing units (GPUs) is presented. MV adaptive beamforming technique is attractive as it is capable of producing high quality images with narrow mainlobe width and low sidelobe level. However, because of its substantially higher computational requirements, realizing MV in real-time has been prohibitively difficult. Recent advancements in commodity GPUs have made very high performance computing possible at very affordable price. Using a commercial off-the-shelf GPU, an MV beam-former achieving real-time performance has been realized. Tradeoffs between computational throughput and image quality have been studied. Careful selection of algorithm parameters, including receive aperture and sub-aperture size, was demonstrated to be imperative for achieving real-time performance without sacrificing image qualities.published_or_final_versionThe 2011 IEEE International Ultrasonics Symposium (IUS), Orlando, FL., 18-21 October 2011. In IEEE International Ultrasonics Symposium Proceedings, 2011, p. 474-47

Portable parallel kernels for high-speed beamforming in synthetic aperture ultrasound imaging

In medical ultrasound, synthetic aperture (SA) imaging is well-considered as a novel image formation technique for achieving superior resolution than that offered by existing scanners. However, its intensive processing load is known to be a challenging factor. To address such a computational demand, this paper proposes a new parallel approach based on the design of OpenCL signal processing kernels that can compute SA image formation in real-time. We demonstrate how these kernels can be ported onto different classes of parallel processors, namely multi-core CPUs and GPUs, whose multi-thread computing resources are able to process more than 250 fps. Moreover, they have strong potential to support the development of more complex algorithms, thus increasing the depth range of the inspected human volume and the final image resolution observed by the medical practitioner.published_or_final_versio