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The 3-D ultrasound imaging provides distinct advantages over its 2-D counterpart leading to a more accurate analysis of tumors and cysts. However, the front end of a 3-D system must receive and process data at prodigious rates, making it impractical for power-constrained portable systems. Synthetic aperture sequential beamforming (SASB) is an ultrasound beamforming technique that splits the computation into two stages, such that the computation in Stage 1 can be completed in the power-constrained front end while the remaining computation can be done elsewhere. In this article, we present several algorithmic and architectural techniques to enable efficient computation of Stage 1 processing without compromising imaging quality. Specifically, we present algorithmic techniques that reduce the computational complexity in Stage 1 by $17\times $ through a systematic reduction in the number of apodization coefficients. We propose a 3-D die stacked architecture where the signals received by 961 active transducers are digitized, routed by a network-on-chip, and processed in parallel. This architecture does not require the explicit storage of incoming data samples. We synthesize the architecture using TSMC 28-nm technology node. The front-end power consumption is around 1.5 W, making it suitable for portable applications.

We have investigated limited angle transmission tomography to estimate speed of sound (SOS) distributions for breast cancer detection. That requires both accurate delineations of major tissues, in this case by segmentation of prior B-mode images, and calibration of the relative positions of the opposed transducers. Experimental sensitivity evaluation of the reconstructions with respect to segmentation and calibration errors is difficult with our current system. Therefore, parametric studies of SOS errors in our bent-ray reconstructions were simulated. They included mis-segmentation of an object of interest or a nearby object, and miscalibration of relative transducer positions in 3D. Close correspondence of reconstruction accuracy was verified in the simplest case, a cylindrical object in homogeneous background with induced segmentation and calibration inaccuracies. Simulated mis-segmentation in object size and lateral location produced maximum SOS errors of 6.3% within 10 mm diameter change and 9.1% within 5 mm shift, respectively. Modest errors in assumed transducer separation produced the maximum SOS error from miscalibrations (57.3% within 5 mm shift), still, correction of this type of error can easily be achieved in the clinic. This study should aid in designing adequate transducer mounts and calibration procedures, and in specification of B-mode image quality and segmentation algorithms for limited angle transmission tomography relying on ray tracing algorithms.

Current segmentation networks based on the encoder-decoder architecture have tried recovering spatial information by stacking convolution blocks in the decoder. Unconventionally, we consider that iteratively exploiting spatial attention from high stage to refine lower stage features can form an attention-driven mechanism to step-wise recover detailed features. In this paper, we rethink image segmentation from a novel perspective: a process of step-wise focusing on targets. We develop a lightweight Focus Module (FM) and present a powerful transplantable Step-wise Focus Network (SFN) for biomedical image segmentation. FM extracts high-level spatial attention and combines it with low-level features by our proposed focus learning to generate revised features. Our SFN extends U-Net encoder sub-network and employs just FMs to construct a focus path in order to consistently refine features. We evaluate SFNs in comparison with U-Net and other state-of-art methods on multiple biomedical image segmentation benchmarks. While using 30% floating-point operations and 60% parameters of U-Net, SFNs achieve great performances without any postprocessing.

Synthetic aperture sequential beamforming (SASB) is a two-stage process, with fixed transmit and receive beamforming in the first stage, followed by dynamic receive beamforming in the second stage. Compared to 3D synthetic aperture ultrasound (SAU) imaging, 3D SASB has low computational complexity at the front-end, making it suitable for portable devices. Unfortunately, 3D SASB has low volume rate since typically only one subaperture transmits and receives at a time. To increase the volume rate, we propose to transmit and receive multiple subapertures simultaneously. A straight-forward implementation of such a scheme, for even four simultaneous firings, results in an increase in grating lobe and sidelobe levels. To address these issues, we use bin-based random sparse array to reduce the grating lobes caused by the three other transmits, and then optimize the locations of the active receive elements to minimize the sidelobe. Compared to a contemporary 3D SASB method, the proposed multiple-firing sparse array method increases the volume rate from 11 to 45 volumes per second, without increasing computational complexity at the front-end and with only a small degradation in imaging quality.

3D ultrasound is becoming common for noninvasive medical imaging because of its high accuracy, safety, and ease of use. Unlike other modalities, ultrasound transducers require little power, which makes handheld imaging platforms possible, and several low-resolution 2D devices are commercially available today. However, the extreme computational requirements (and associated power requirements) of 3D ultrasound image formation have, to date, precluded handheld 3D-capable devices. The authors describe the Sonic Millip3De, a new system architecture and accelerator for 3D ultrasound beamforming--the most computationally intensive aspect of image formation. Their three-layer die-stacked design combines a new approach to the ultrasound imaging algorithm better suited to hardware with a custom beamforming accelerator that employs massive data parallelism and a streaming pipeline architecture to achieve high-quality 3D ultrasound imaging within a full-system power of 15 W in 45-nm semiconductor technology (400× less than a conventional DSP solution). Under anticipated scaling trends, the authors project that Sonic Millip3De will achieve the target 5-W power budget by the 16-nm technology node.

Synthetic aperture sequential beamforming (SASB) is a technique to achieve range-independent resolution in 2D images with lower computational complexity compared to synthetic aperture ultrasound (SAU). It is a two stage process, wherein the first stage performs fixed-focus beamforming followed by dynamic-focus beamforming in the second stage. In this work, we extend SASB to 3D imaging and propose two schemes to reduce its complexity:(1) reducing the number of elements in both transmit and receive and (2) implementing separable beamforming in the second stage. Our Field-II simulations demonstrate that reducing transmit and receive apertures to 32×32 and 16×16 elements, respectively, and using separable beamforming reduces 3D SASB computational complexity by 15× compared to the 64×64 aperture case with almost no loss in image quality. We also describe a hardware architecture for 3D SASB that performs first-stage beamforming in the scan head, reducing the amount of data that must be transferred for offchip processing in the second stage beamformer by up to 256×. We describe an implementation approach for the second stage that performs an optimized in-place update for both steps of separable beamforming and is well suited for GPU.

Plane wave imaging can provide high frame rates and is widely used for fast imaging in medical ultrasound. Due to a lack of transmit focus, its image quality is usually worse than other ultrasonic imaging modalities, such as Synthetic Aperture Ultrasound. In practice, images with high contrast-to-noise ratio (CNR) are highly desirable as they make it possible for the sonographer to detect small cysts with better accuracy. In this work, we propose to use edge detection and smoothing filters to improve the CNR of cyst images while keeping the point spread function unchanged after beamforming. We show that our post-processing technique helps achieve CNR larger than 19 dB for cyst images with 75 firing angles compounded.

3D blood velocity estimation in medical ultrasound systems is revolutionizing the diagnosis of vascular diseases. However, the accuracy of blood velocity estimation is greatly affected by clutter signals from the vessel wall and the tissues surrounding the vessel. Filters used today to remove clutter are computationally expensive, limiting their practicality in portable 3D systems. In this paper, we present clutter filters for arterial flow that reduce computational complexity by orders of magnitude while maintaining the clutter removal performance of existing techniques. We achieve this goal by combining the existing Hankel-SVD clutter filter with the power iteration method to eliminate unnecessary SVD calculations. For the filters which use power iteration exclusively, we achieve excellent filtering performance with only 14.2% computational overhead to our previous flow estimation system. With these filtering methods, our pipelined architecture can compute velocity fields at a rate of 85 frames per second.

3D ultrasound is common for non-invasive medical imaging in cardiology and OB-GYN because of its accuracy, safety, and real-time ease of use. However, high bandwidth requirements and extreme computational complexity have precluded hand-held and low-power 3D systems, limiting 3D applications. In previous work, we presented Sonic Millip3De, a hardware design that can efficiently handle the high computational demand of real-time 3D synthetic aperture beamforming, even in handheld and mobile applications. The design combines a custom, highly parallel hardware system with a novel delay approximation method to quickly produce high quality 3D image data within an estimated 15 W full-system power budget. Prior evaluations of the design relied on software prototypes; this work extends previous evaluations with an FPGA implementation of the beamforming accelerator, validating the results of earlier prototypes. In particular, we carry out image quality analyses of our beamforming architecture using simulated 3D echo data (from Field II) and 2D artificial tissue phantom data acquired using a Verasonics V-1 system and Philips P4-1 probe. We compare results from the FPGA implementation to an ideal software beamformer and prior software prototypes of the Sonic Millip3De design.

Vector flow imaging is a critical component in the clinical diagnosis of cardiovascular diseases; however, most current methods are too computationally expensive to scale well to 3D. Less complex techniques, such as Doppler-based imaging (which cannot provide lateral flow measurements) and basic speckle tracking algorithms (which have poor lateral accuracy), are incapable of producing high quality 3D measurements. In this paper, we first extend a technique designed to improve lateral flow accuracy for 2D velocity vector estimation, the synthetic lateral phase method, to 3D (SLP-3D). We then show that a straightforward implementation of this algorithm is too computationally complex for modern systems. Instead, we propose a two-tiered method that uses low complexity sum-of-absolute differences (SAD) for coarse-grained search and an optimized version of SLP-3D to fine tune the search for sub-pixel accuracy. We show that the proposed method (SAD+SLP-3Dopt) achieves a 9× reduction in computational complexity compared to the naive SLP-3D. Field II simulations for plug and parabolic flow using our method show a fairly high degree of accuracy in both the axial and the lateral components. Finally, we show our technique can support accurate flow imaging with up to 130 velocity estimations/sec within the power constraints of a handheld device.

3D plane-wave imaging systems can support the high volume acquisition rates that are essential for 3D vector flow imaging and sonoelastography but suffer from low resolution and low SNR. Coherent compounding is a technique to improve the image quality of plane-wave systems at the expense of significant increase in beamforming computational complexity. In this paper, we propose a new separable beamforming method for 3D plane-wave imaging with coherent compounding that has computational complexity comparable to that of a non-separable non-compounding baseline system. The new method with 9-fire-angle compounding helps improve average CNR from 1.6 to 2.2 and achieve a SNR increase of 9.0 dB compared to the baseline system. We also propose several enhancements to our beamforming accelerator, Sonic Millip3De, including additional SRAM arrays, configurable interconnect, and embedded DRAM. Overall, our system is capable of generating high resolution images at 1000 volumes per second.

3D ultrasound is becoming common for non-invasive medical imaging because of its accuracy, safety, and ease of use. However, the extreme computational requirements (and associated power requirements) of image formation for a large 3D system have, to date, precluded hand-held 3D-capable devices. Sonic Millip3De is a recently proposed hardware design that leverages modern computer architecture techniques, such as 3D die stacking, massive parallelism, and streaming data flow, to enable high-resolution synthetic aperture 3D ultrasound imaging in a single, low-power chip. In this paper, we enhance Sonic Millip3De with a new virtual source firing sequence and dynamic receive focusing scheme to optimize receive apertures in multiple depth focal zones. These enhancements further reduce power requirements while maintaining image quality over a large depth range. We present image quality analysis using Field II simulations of cysts in tissue at varying depths to show that our methods do not degrade CNR relative to an ideal system with no power constraints. Then, using RTL-level design for an industrial 45nm ASIC process, we demonstrate 3D synthetic aperture with 120×88 transducer array within a 15W full-system power budget (400x less than a conventional DSP solution). We project that continued semicondutor scaling will enable a sub-5W power budget in 16nm technology.

Three-dimensional (3D) ultrasound is becoming common for non-invasive medical imaging because of its high accuracy, safety, and ease of use. Unlike other modalities, ultrasound transducers require little power, which makes hand-held imaging platforms possible, and several low-resolution 2D devices are commercially available today. However, the extreme computational requirements (and associated power requirements) of 3D ultrasound image formation has, to date, precluded hand-held 3D capable devices. We describe the Sonic Millip3De, a new system architecture and accelerator for 3D ultrasound beamformation-the most computationally intensive aspect of image formation. Our three-layer die-stacked design features a custom beamsum accelerator that employs massive data parallelism and a streaming transform-select-reduce pipeline architecture enabled by our new iterative beamsum delay calculation algorithm. Based on RTL-level design and floorplanning for an industrial 45nm process, we show Sonic Millip3De can enable 3D ultrasound with a fully sampled 128×96 transducer array within a 16W full-system power budget (400× less than a conventional DSP solution) and will meet a 5W safe power target by the 11nm node.

In this paper, we propose several techniques to reduce the computation complexity of orthogonal chirp and orthogonal Olay code based synthetic aperture ultrasound systems. First, we minimize the complexity in terms of number of effective multiplications by choosing the system parameters for a specified SNR gain. The proposed method helps in reducing the complexity by about 20. Next, we consider a system that compensates for body motion. We reduce the complexity of motion compensation first by doing the calculations in polar domain, and second, by making use of the correlation in motion velocity field in a small neighborhood. These approximations reduce the computation complexity by3000 with minimal performance penalty.

In addition to surface plasmon polaritons (SPPs), quasi-cylindrical waves (CWs) are also important components of electromagnetic fields on metal surfaces. In this study, we present a closed-form expression for CW fields on a dielectric-film-coated metal surface. It is found that the effective refractive index of CWs roughly keeps unchanged when the coated dielectric film becomes thicker, while the effective refractive index of SPPs increases rapidly. These different responses are explained by referring to a waveguide perspective, in which the SPP and CW waves are, respectively, identified as a waveguide mode and superposition of radiation modes. The results and related analyses with the waveguide perspective explicitly show the different physical natures of SPPs and CWs.