Anup Agarwal

A Fully Programmable Computing Architecture for Medical Ultrasound Machines

Application-specific ICs have been traditionally used to support the high computational and data rate requirements in medical ultrasound systems, particularly in receive beamforming. Utilizing the previously developed efficient front-end algorithms, in this paper, we present a simple programmable computing architecture, consisting of a field-programmable gate array (FPGA) and a digital signal processor (DSP), to support core ultrasound signal processing. It was found that 97.3% and 51.8% of the FPGA and DSP resources are, respectively, needed to support all the front-end and back-end processing for B-mode imaging with 64 channels and 120 scanlines per frame at 30 frames/s. These results indicate that this programmable architecture can meet the requirements of low- and medium-level ultrasound machines while providing a flexible platform for supporting the development and deployment of new algorithms and emerging clinical applications.

Fast JPEG 2000 decoder and its use in medical imaging

Over the last decade, a picture archiving and communications system (PACS) has been accepted by an increasing number of clinical organizations. Today, PACS is considered as an essential image management and productivity enhancement tool. Image compression could further increase the attractiveness of PACS by reducing the time and cost in image transmission and storage as long as 1) image quality is not degraded and 2) compression and decompression can be done fast and inexpensively. Compared to JPEG, JPEG 2000 is a new image compression standard that has been designed to provide improved image quality at the expense of increased computation. Typically, the decompression time has a direct impact on the overall response time taken to display images after they are requested by the radiologist or referring clinician. We present a fast JPEG 2000 decoder running on a low-cost programmable processor. It can decode a losslessly compressed 2048/spl times/2048 CR image in 1.51 s. Using this kind of a decoder, performing JPEG 2000 decompression at the PACS display workstation right before images are displayed becomes viable. A response time of 2 s can be met with an effective transmission throughput between the central short-term archive and the workstation of 4.48 Mb/s in case of CT studies and 20.2 Mb/s for CR studies. We have found that JPEG 2000 decompression at the workstation is advantageous in that the desired response time can be obtained with slower communication channels compared to transmission of uncompressed images.

New Demodulation Method for Efficient Phase-Rotation-Based Beamforming

In this paper, we present a new demodulation method to reduce hardware complexity in phase-rotation- based beamforming. Due to its low sensitivity to phase delay errors, quadrature demodulation, which consists of mixing and lowpass filtering, is commonly used in ultrasound machines. However, because it requires two lowpass filters for each channel to remove harmonics after mixing, the direct use of quadrature demodulation is computationally expensive. To alleviate the high computational requirement in quadrature demodulation, we have developed a two-stage demodulation technique in which dynamic receive focusing is performed on the mixed signal instead of the complex baseband signal. Harmonics then are suppressed by using only two lowpass filters. When the number of channels is 32, the proposed two-stage demodulation reduces the necessary number of multiplications and additions for phase-rotation beamforming by 82.7% and 88.2%, respectively, compared to using quadrature demodulation. We have found from simulation and phantom studies that the proposed method does not incur any significant degradation in image quality in terms of axial and lateral resolution. These preliminary results indicate that the proposed two-stage demodulation method could contribute to significantly reducing the hardware complexity in phase-rotation-based beamforming while providing comparable image quality.

P2D-6 Ultrasound Color Doppler Imaging on a Fully Programmable Architecture

Ultrasound color Doppler imaging is widely used for real-time evaluation of blood flow in a user-specified region of interest. However, it is computationally expensive and burdensome for low-end ultrasound machines. In this paper, we have investigated the feasibility of performing color Doppler processing on a low-cost programmable architecture consisting of a field programmable gate array (FPGA) (e.g., Cyclone II, Altera, San Jose, CA) and a digital signal processor (DSP) (e.g., TMS320C64x, Texas Instruments, Dallas, TX). From the feasibility study, we have found that only 63.8% and 49.2% of the resources in the FPGA and DSP, respectively, are utilized to support all the digital processing (i.e., front-end and back-end) for color Doppler imaging with a typical system configuration for portable ultrasound machines. These results indicate that a low-cost programmable architecture can meet the requirements of front-end and back-end processing in ultrasound color Doppler imaging

Adaptive field-of-view imaging for efficient receive beamforming in medical ultrasound imaging systems

Quadrature demodulation-based phase rotation beamforming (QD-PRBF) is commonly used to support dynamic receive focusing in medical ultrasound systems. However, it is computationally demanding since it requires two demodulation filters for each receive channel. To reduce the computational requirements of QD-PRBF, we have previously developed two-stage demodulation (TSD), which reduces the number of lowpass filters by performing demodulation filtering on summation signals. However, it suffers from image quality degradation due to aliasing at lower beamforming frequencies. To improve the performance of TSD-PRBF with reduced number of beamforming points, we propose a new adaptive field-of-view (AFOV) imaging method. In AFOV imaging, the beamforming frequency is adjusted depending on displayed FOV size and the center frequency of received signals. To study its impact on image quality, simulation was conducted using Field II, phantom data were acquired from a commercial ultrasound machine, and the image quality was quantified using spatial (i.e., axial and lateral) and contrast resolution. The developed beamformer (i.e., TSD-AFOV-PRBF) with 1024 beamforming points provided comparable image resolution to QD-PRBF for typical FOV sizes (e.g., 4.6% and 1.3% degradation in contrast resolution for 160 mm and 112 mm, respectively for a 3.5 MHz transducer). Furthermore, it reduced the number of operations by 86.8% compared to QD-PRBF. These results indicate that the developed TSD-AFOV-PRBF can lower the computational requirement for receive beamforming without significant image quality degradation.

Image quality evaluation with a new phase rotation beamformer

Over the last few decades, dynamic focusing based on digital receive beamforming (DRBF) has led to significant improvements in image quality. However, it is computationally very demanding due to its requirement for multiple lowpass filters (e.g., a complex filter for each receive channel in quadrature demodulation-based phase rotation beamform- ers (QD-PRBF)). We recently developed a novel phase rotation beamformer with reduced complexity, which can lower: 1) the number of lowpass filters using 2-stage demodulation (TSD) and 2) the number of beamforming points using adap tive field-of-view (AFOV) imaging. In TSD, dynamic focusing is performed on the mixed signals, while sampling frequency of the beamformed signal (i.e., beamforming frequency) is adjusted based on the displayed field-of-view (FOV) size in AFOV imaging. In this paper, the image quality of the developed beamformer (i.e., TSD-AFOV-PRBF) has been quantitatively evaluated using phantom and in vivo data. From the phantom study, it was found that TSD-AFOV-PRBF with only 1024 beamforming points provides comparable image quality to QD-PRBF. We obtained a median contrast resolution (CR) degradation of 7.6% for the FOV size of 160 mm. Image quality steadily improves with FOV size reduction (e.g., 2.3% CR degradation at 85 mm). Similar results were also obtained from an in vivo study. Thus, TSD-AFOV-PRBF could provide comparable image quality to conventional beamformers at considerably reduced computational cost.

Ultrasound Machine for Distributed Diagnosis and Home Use

In this paper, we present a home ultrasound machine that could be used in a distributed diagnosis and home healthcare (D2H2) setting. It will enable remote screening, diagnosis and monitoring of the patient by addressing limitations of the current practice and lead to improved healthcare delivery. For the home ultrasound machine, we have developed a reconfigurable and programmable architecture and efficient front-end algorithms to significantly reduce the hardware complexity while providing improved flexibility to adapt to different clinical applications. Several technical and non-technical challenges for realization of the home ultrasound machine setting are also discussed

P3G-7 Adaptive Field-of-View Imaging for Efficient Phase Rotation Beamforming

Digital quadrature demodulation (QD)-based phase rotation beamforming (PRBF) is commonly used in ultrasound machines due to its low sensitivity to phase delay errors. However, it is very expensive computationally. To alleviate this high computational requirement during the QD, we have previously developed two efficient methods, two-stage demodulation (TSD) and multi-stage uniform coefficient (MSUC) filter. In this paper, we present an adaptive field-of-view (FOV) imaging method, which dynamically varies the beamforming frequency based on the FOV of display. When the number of channels is 32 and the number of beamforming points is 512, the proposed method lowers the complexity of the MSUC- and the TSD-based PRBF by 26.2% and 65.3%, respectively, in terms of the number of operations. The image quality with adaptive FOV imaging has been evaluated using simulation and in vivo data. Adaptive FOV imaging with the MSUC-based PRBF provides comparable contrast resolution (CR) to the QD-based PRBF for various FOV sizes (e.g., CR degradation of 0.4% and 0.01% was obtained for the FOV size of 160 mm and 85 mm, respectively). Adaptive FOV imaging with the TSD-based PRBF suffers from some degradation in image quality for the large FOV (i.e., 4.3% degradation in CR). On the other hand, it provides comparable image quality for the smaller FOV (i.e., 0.5% degradation in CR). These preliminary results indicate that the adaptive FOV imaging method has good potential to further reduce the hardware complexity of the PRBF based on MSUC and TSD