Sunmi Yeo

A new smart probe system for a tablet PC-based point-of-care ultrasound imaging system: Feasibility study

There is a growing interest in a hand-held ultrasound (US) system for a point-of-care diagnosis. In this paper, we present the hand-held smart US probe system, which includes analog and digital front-ends, mid-processor, and interface. In the analog front-end, 16 channels could be implemented using two eight-channel high-voltage pulsers and analog-to-digital converters (ADC). The following digital front-end was implemented using a single low-cost field programmable gate array chip (FPGA). The output data from the digital front-end are transferred to the commercial tablet PC via the USB 3.0 interface. The tablet PC performs the back-end processing and image display on a graphical user interface (GUI). The smart probe system developed can provide the real-time B-mode images up to 22 Hz of frame rate with 7 W of estimated maximum power consumption. The weight and dimension of the developed system are 73 g and 150 × 40 × 10 mm3 in length, width, and height, respectively. To evaluate the performance of the proposed smart probe system, the phantom and in vivo experiments were conducted.

New Adaptive Clutter Rejection Based on Spectral Analysis for Ultrasound Color Doppler Imaging: Phantom and In Vivo Abdominal Study

Effective rejection of time-varying clutter originating from slowly moving vessels and surrounding tissues is important for depicting hemodynamics in ultrasound color Doppler imaging (CDI). In this paper, a new adaptive clutter rejection method based on spectral analysis (ACR-SA) is presented for suppressing nonstationary clutter. In ACR-SA, tissue and flow characteristics are analyzed by singular value decomposition and tissue acceleration of backscattered Doppler signals to determine an appropriate clutter filter from a set of clutter filters. To evaluate the ACR-SA method, 20 frames of complex baseband data were acquired by a commercial ultrasound system equipped with a research package (Accuvix V10, Samsung Medison, Seoul, Korea) using a 3.5-MHz convex array probe by introducing tissue movements to the flow phantom (Gammex 1425 A LE, Gammex, Middleton, WI, USA). In addition, 20 frames of in vivo abdominal data from five volunteers were captured. From the phantom experiment, the ACR-SA method provided 2.43 dB (p <; 0.001) and 1.09 dB ( ) improvements in flow signal-to-clutter ratio (SCR) compared to static (STA) and down-mixing (ACR-DM) methods. Similarly, it showed smaller values in fractional residual clutter area (FRCA) compared to the STA and ACR-DM methods (i.e., 2.3% versus 5.4% and 3.7%, respectively, ). The consistent improvements in SCR from the proposed ACR-SA method were obtained with the in vivo abdominal data (i.e., 4.97 dB and 3.39 dB over STA and ACR-DM, respectively). The ACR-SA method showed less than 1% FRCA values for all in vivo abdominal data. These results indicate that the proposed ACR-SA method can improve image quality in CDI by providing enhanced rejection of nonstationary clutter.Effective rejection of time-varying clutter originating from slowly moving vessels and surrounding tissues is important for depicting hemodynamics in ultrasound color Doppler imaging (CDI). In this paper, a new adaptive clutter rejection method based on spectral analysis (ACR-SA) is presented for suppressing nonstationary clutter. In ACR-SA, tissue and flow characteristics are analyzed by singular value decomposition and tissue acceleration of backscattered Doppler signals to determine an appropriate clutter filter from a set of clutter filters. To evaluate the ACR-SA method, 20 frames of complex baseband data were acquired by a commercial ultrasound system equipped with a research package (Accuvix V10, Samsung Medison, Seoul, Korea) using a 3.5-MHz convex array probe by introducing tissue movements to the flow phantom (Gammex 1425 A LE, Gammex, Middleton, WI, USA). In addition, 20 frames of in vivo abdominal data from five volunteers were captured. From the phantom experiment, the ACR-SA method provided 2.43 dB (p <; 0.001) and 1.09 dB ( ) improvements in flow signal-to-clutter ratio (SCR) compared to static (STA) and down-mixing (ACR-DM) methods. Similarly, it showed smaller values in fractional residual clutter area (FRCA) compared to the STA and ACR-DM methods (i.e., 2.3% versus 5.4% and 3.7%, respectively, ). The consistent improvements in SCR from the proposed ACR-SA method were obtained with the in vivo abdominal data (i.e., 4.97 dB and 3.39 dB over STA and ACR-DM, respectively). The ACR-SA method showed less than 1% FRCA values for all in vivo abdominal data. These results indicate that the proposed ACR-SA method can improve image quality in CDI by providing enhanced rejection of nonstationary clutter.

Advanced functional flow index imaging using planewave excitation: Phantom study

In conventional ultrasound imaging, the quantitative information of vascular hemodynamics, e.g., resistive index (RI) and pulsatility index (PI), is provided by a spectral Doppler mode. However, achieving the Doppler indices with spectral Doppler imaging is time consuming and has limitation on accuracy when scanning various vascular regions. In this paper, a new functional flow index imaging (FFII) method with plane wave excitation is proposed. In the proposed FFII method, by transmitting a plane wave, sufficient temporal samples on a two-dimensional plane can be obtained during one cardiac cycle. To measure functional indices, the velocity of blood flow is calculated via an auto-correlation method. Then, the RI and PI values are extracted from the estimated blood velocities. In FFII, the measured RI and PI values are visualized as a two-dimensional pseudo color image. To evaluate the performance of the proposed method, pre-beamformed radio-frequency data from a flow phantom were acquired using a commercial ultrasound scanner with a research package. The mean RI and PI values from the proposed method were compared with those from the conventional spectral Doppler method. The maximum error was less than 3%. These results indicate that the proposed FFII method can provide a two-dimensional functional index image with a high frame rate.

Analysis of angle compounding on a fast color Doppler imaging: Phantom study

Fast color Doppler imaging (CDI) based on plane wave excitation and angle compounding is useful for evaluating vascular diseases with high frame rates. Due to limited spatial resolution from plane wave excitation, the image quality of CDI is substantially degraded. To enhance the spatial resolution, angle compounding, in which several tiled plane waves are excited and coherently summed together during receive beamforming, can be used. However, the effect of angle compounding on fast CDI has not been extensively analyzed. In this paper, the analysis of angle compounding on fast CDI with phantom studies is presented. To evaluate the effect of the angle compounding, in this paper, a new color Doppler imaging technique based on sliding angle compounding (CDI-SAC) is adopted. In CDI-SAC, the angle compounding is updated as each new angle compounding is acquired so that there is no reduction in both Doppler pulse-repetition frequency (PRF) and frame rate. For that reason, the CDI-SAC method is used for the analysis of angle compounding on fast CDI. The PRF of 2 kHz and four different sets of compounding angles (i.e., 3, 6, 8 and 12) were used for generating a color Doppler image. The results of each angle compounding from CDI-SAC shows improved hemodynamic representation as the number of combined angle increases. The measured root mean square errors (RMSEs) for three angle sets (3, 6, and 8) by assuming the 12 angle set as the reference are 0.0124, 0.0107 and 0.0082, respectively. These results indicate that the proper selection of the number of angles in fast color Doppler imaging is important for improving spatial resolution while reducing the blocky artifacts.

New adaptive clutter rejection based on spectral decomposition and tissue acceleration for ultrasound color Doppler imaging

In ultrasound color Doppler imaging(CDI), effective clutter rejection is essential for estimating flow velocity and power. Since the clutter has time-varying characteristics, it is challenging to suppress it with a static clutter filter. In this paper, a new adaptive clutter rejection method based on spectral decomposition and tissue acceleration (ACR) for suppressing nonstationary clutter is presented. In the proposed method, tissue and flow characteristics are analyzed from singular value decomposition of backscattered Doppler signals to select optimal clutter filter from a bank of clutter filters. To evaluate the ACR method, phantom and in vivo experiments were conducted. For the phantom experiments, 20 frames of complex baseband data were acquired with a commercial ultrasound system (V10, Samsung Medison, Seoul, Korea) using a 3.5-MHz convex array probe by tapping over the flow phantom (Gammex 1425A LE, Gammex, Middleton, WI, USA) surface to mimic tissue movements. Similarly, 20 frames of in vivo liver data from a volunteer were also acquired. The performance of the proposed ACR method was compared with conventional clutter rejection methods, i.e., static (ST) and down-mixing (DM), using a commonly-used flow signal-to-clutter ratio (SCR) and fractional residual clutter area (FRCA). From the phantom experiments, the ACR method provided 2.03 dB and 0.98 dB improvements in SCR over the ST and DM methods. Similarly, ACR showed improvements in fractional residual clutter area (FRCA) compared to the ST and DM methods (i.e., 2.3% vs. 5.4 % and 3.7%, respectively). The consistent results were obtained with the in vivo experiments. The improvement in SCR from the ACR method is 4.90 dB and 3.98 dB, compared to the ST and DM methods. In addition, the ACR method showed less than 1% FRCA values for all 20 frames of in vivo data. These results indicate that the proposed ACR based on spectral decomposition and tissue acceleration can improve image quality in ultrasound color Doppler imaging by effectively removing the clutter.