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IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control , vol. 59, no. 7, July 2012
A Single FPGA-Based Portable
Ultrasound Imaging System
for Point-of-Care Applications
Gi-Duck Kim, Changhan Yoon, Sang-Bum Kye, Youngbae Lee, Jeeun Kang,
Yangmo Yoo, and Tai-kyong Song
Abstract—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 FPGAbased 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.
I. Introduction
P
oint-of-care (POC) diagnostic imaging systems allow clinicians to access and diagnose a patient at the
scene of an accident or at the patient’s bedside because of
their improved accessibility [1], [2]. In addition, these POC
imaging systems have the potential to effectively address
the challenges in healthcare disparities arising from current central, provider-centric, and hospital-based healthcare delivery. Desirable features of the POC diagnostic
imaging systems include safety, price, portability, and ease
of use [3]. Conventional X-rays, CT, and magnetic resonance imaging tools are not portable, and they are more
suitable in centralized locations, e.g., hospitals and clinics,
because of their size, cost, and the training required to
operate them. On the other hand, ultrasound imaging is
safe, noninvasive, portable, less expensive, relatively easy
to use, and capable of real-time imaging [4].
Several portable ultrasound machines have been developed and deployed in various emerging POC applications,
such as ambulatory and intensive care [5]. To achieve minManuscript received September 25, 2011; accepted February 15, 2012.
This research was partially supported by the BK21 program, IC Design Education Center (IDEC), and the Converging Research Center
Program through the Ministry of Education, Science and Technology
(2011K000716), Republic of Korea.
The authors are with the Department of Electronic Engineering, Sogang University, Seoul, Korea (e-mail: ymyoo@sogang.ac.kr and tksong@
sogang.ac.kr).
Y. Yoo is also with the Interdisciplinary Program of Integrated Biotechnology, Sogang University, Seoul, Korea.
DOI http://dx.doi.org/10.1109/TUFFC.2012.2339
iaturization and cost reduction as well as longer battery
life, these portable ultrasound machines take advantage of
the continuing advances in solid-state technologies, such
as application-specific integrated circuits (ASICs) [6].
However, because the ASIC approach is typically beneficial to well-defined targeted applications (e.g., consumer
electronics), its usefulness for the emerging POC diagnostic imaging systems would be limited [7]. Moreover, it is
necessary to have improved functional flexibility in the
POC imaging systems for adapting quickly to continuously evolving clinical applications.
Previously, the programmable ultrasound system architecture was proposed, in which digital signal processors
(DSPs) are used for performing core ultrasound signal and
image processing [8], [9]. Because of improved flexibility
and efficiency, the programmable ultrasound system can
quickly test new clinical imaging modes and algorithms
[10]–[12]. In addition, the programmable approach has
been evaluated for POC diagnostic imaging systems, especially computational capabilities [13], [14]. However, these
evaluations were inconclusive because they were conducted with commercially available testing boards, instead of
building a prototypical device. Furthermore, it is challenging to perform front-end processing (i.e., beamforming)
on a single DSP because of its limited data transfer bandwidth and processing performance [15].
Various methods have been proposed to miniaturize the
ultrasound imaging system [16], [17], [18]. The delta-sigma oversampled beamforming method was proposed and
implemented in a field-programmable gate array (FPGA)
[16], [17]. Because of its low hardware complexity (digital
logic), the beamformer with up to 57 channels could be
implemented in a single Virtex-E FPGA (Xilinx Inc., San
Jose, CA). Although the delta-sigma oversampled beamforming method can reduce the overall hardware complexity in the analog circuit and digital logic (i.e., beamformer), this method is not suitable for low-cost FPGA
because it requires a high operating clock frequency to
obtain a sufficient SNR [19]. The direct sampled in-phase/
quadrature (DSIQ) beamforming method can also reduce
the hardware complexity [18]. In DSIQ, the second-order
sampling is used to obtain in-phase and quadrature components, and receive focusing is conducted by using phase
rotation. However, the DSIQ beamforming method yields
degraded image quality because it assumes a narrowband
signal, which is typically not satisfied in medical ultrasound imaging [20], [21].
0885–3010/$25.00 © 2012 IEEE
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kim et al.: FPGA-based portable ultrasound imaging system
In this paper, we present our low-cost portable ultrasound system working as a standalone device, in which
a single FPGA is employed. In the prototype portable
system, all the ultrasound signal and image processing
modules, including an effective 32-channel receive beamformer with extended aperture (EA), are embedded in a
Spartan-3 FPGA (Xilinx Inc.). In addition, a Samsung
S3C6410 mobile processor (Samsung Group, Suwon, Korea) running Linux at 667 MHz serves as a system controller. Cost-effective algorithms, such as pseudo-dynamic
receive beamforming and look-up table (LUT)-based processing, are used for reducing the hardware complexity in
ultrasound signal and image processing. The performance
of the low-cost portable ultrasound system developed was
evaluated with Field II simulation and phantom experiments.
II. Methods
A. System Overview
Fig. 1 shows an overall system block diagram of the
developed low-cost portable ultrasound imaging system
using a single FPGA. As shown in Fig. 1, the portable system developed is composed of an ultrasound scanner module and a power supply/battery module. The 16-channel
ultrasound scanner module consists of analog front-end
circuits [i.e., analog receivers, analog-to-digital converters
(ADCs) and transmit pulsers], and a Spartan-3 FPGA
chip. The ultrasound scanner presented can provide the
equivalent image quality of a 32-channel ultrasound system by using an EA technique. The analog front-end circuits in the developed portable ultrasound system include
eight pulser drivers, 16 high-voltage (HV) pulsers, eight
HV multiplexers (MUXs), and two eight-channel 12-bit
ADC chips running at 40 MHz with a low-voltage differential signaling interface. The Spartan-3 FPGA is used
for supporting receive beamforming and mid and backend B-mode processing. In addition, it is used for generating transmit pulse pattern for transmit focusing. The
real-time controller is also incorporated in the FPGA for
the interface between the system controller and the ultrasound transmit and receive modules (e.g., pulse-repetition
frequency clock generation and synchronization among
various modules). The Samsung S3C6410 mobile processor running Linux is used for controlling all the subsystems in the portable ultrasound system developed, including image display and communication.
1387
Fig. 1. System block diagram of the low-cost portable ultrasound based
on a single field-programmable gate array (FPGA).
where rbf(n) is the beamformed receive signal, D is the
number of the physical channels in receive beamforming,
N is the number of focusing points along the receive scanline, rd(n) is the receive signal from the dth channel, ad is
the apodization coefficient, and τd is the receive focusing
delay for the dth channel, respectively. The number of
focusing points N is given by
 2Z

N = floor  × f bf  ,
 c

(2)
where Z is the imaging depth, c is the speed of sound and
fbf is the beamforming frequency. The dth channel receive
focusing delay τd can be obtained by
1
(x d − x f )2 + (z d − z f )2 − z fp(n)  ,
c
n = 1, 2, , N ,
τ d(n) =
(3)
where (xd, zd) are the locations of the dth channel, (xf, zf)
are the locations of the focal point, and zfp is the distance
from the center channel to a focal point along the receive
scanline. In dynamic receive beamforming, as shown in
Fig. 3(a), the focusing delay at (3) is updated for each
beamforming point (i.e., N times) at each channel, leading
to increased hardware complexity.
On the other hand, in the presented low-cost portable
ultrasound imaging system, to lower its hardware complexity, the focusing delay value in (3) is not calculated at
each focal point but updated only at the predetermined
B. Front-End Module
1) Pseudo-Dynamic Receive Beamforming: In medical
ultrasound imaging, the receive beamforming is used for
improving spatial and contrast resolution. As shown in
Fig. 2, the receive beamforming can be represented by
D −1
rbf(n) = ∑ a drd[n − τ d(n)],
d =0
n = 1, 2, …, N ,
(1)
Fig. 2. Receive beamforming in a medical ultrasound imaging system.
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IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control , vol. 59, no. 7, July 2012
increased. In our low-cost portable ultrasound imaging
system, we adopted the EA technique, which has the potential to improve lateral resolution with a small number
of physical receive channels. With the EA technique, the
portable system developed can provide the equivalent image quality of a 32-channel receive beamformer by using
16 channels while sacrificing the frame rate by reducing
it to half of the previous frame rate. Fig. 4 shows the
transmit and receive array patterns for the EA technique
used in the portable system developed. As shown in Fig.
4, the center 16-element array is transmitted twice in the
same scanline direction. On the other hand, in receive,
the center 16-element array is first used for detecting the
backscattered ultrasound signal, and then the neighboring 16-element array is used. Each scanline is generated
by performing receive beamforming with two sequentially
received signals.
C. Mid and Back-End Processing Modules
Fig. 3. Receive focusing delay update pattern for (a) conventional dynamic receive focusing and (b) pseudo-dynamic focusing where only four
focusing delay values are used.
focal points (i.e., pseudo-dynamic receive focusing) depending on the number of focal zones (M) as shown in
Fig. 3(b). For example, as shown in Figs. 3(a) and 3(b),
whereas, in dynamic receive focusing, 12 focusing delay
values are necessary for 12 focal points, only 4 focusing
delay values are required when the 4 focal zones (i.e., M =
4, with 3 shared focusing points) are assumed.
In addition, in our portable ultrasound system, for
miniaturizing the overall system, the receive focusing delay values are generated based on the predetermined focal zone number offline and stored in an LUT. Because
the number of the updated focusing delay value is substantially reduced, all the delay values for the proposed
pseudo-dynamic receive focusing can be stored instead of
calculating them on the fly. Although the number of focal
zones is fixed, the shared focusing points at each zone can
be varied, depending on imaging depth, to reduce the focusing delay errors. Currently, to support the view depth
of 30 cm, a 2-kB LUT is used to store the 1024 focusing
delay values (2 bytes for each delay value) for linear and
convex array transducers for each channel (i.e., total LUT
size of 32 kB) in our portable ultrasound imaging system.
Fig. 5 shows the functional block diagram of mid and
back-end processing for real-time ultrasound B-mode imaging in the portable system developed.
1) Mid Processing: As shown in Fig. 5, dc canceling is
first applied to the post-beamformed data from a receive
beamformer with pseudo-dynamic focusing and then timegain compensation (TGC) and quadrature demodulation
are conducted. In dc canceling, a 32-tap finite impulse
response filter with 16-bit coefficient resolution is used
to cancel out the undesired dc component from ADCs,
and two sequentially received ultrasound data points are
accumulated in the EA processing block. In addition, a
user-defined TGC curve is applied to generate a well-balanced ultrasound B-mode image over the imaging depth.
To obtain complex baseband data for further back-end
processing, the quadrature demodulation is applied. In the
quadrature demodulation, the sinusoidal values for mixing
are precalculated and stored at an LUT. In the portable
ultrasound system developed, the 640-byte LUT is used
for storing one period of 125-kHz cosine and sine signals
that are sampled at 40 MHz. With this LUT, we can generate the multiple of a 125-kHz sinusoidal signal ranging
from 125 to 20 MHz by increasing address (nnext) with
nstep (i.e., nnext = ncurrent + nstep). For example, we can
2) Extended Aperture: In ultrasound receive beamforming, the spatial resolution in the lateral direction (i.e., perpendicular to the ultrasound propagation direction) can
be approximated by [22]
SD lat ∝
λz fp
,
D
(4)
where λ is the wavelength. Therefore, as the number of
physical receive channels corresponding to D increases,
the lateral resolution can be improved. However, the hardware complexity in the receive beamformer is also rapidly
Fig. 4. Extended aperture (EA) technique.
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kim et al.: FPGA-based portable ultrasound imaging system
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E. Power Supply Module
Fig. 5. Functional block diagram of the mid and back-end processing for
real-time ultrasound B-mode imaging in the developed portable ultrasound system.
obtain 3-MHz cosine and sine values for mixing by setting
nstep = 24. With this LUT-based approach, the dynamic
quadrature demodulation can be achieved by dynamically
changing nstep over the depth.
2) Back-End B-Mode Processing: To extract the envelope of the backscattered ultrasound signal, envelope
detection is applied to complex baseband data from the
mid processing module, and then log compression is conducted to reduce the dynamic range in the ultrasound
envelope data. In the portable ultrasound imaging system
developed, a 16-kB LUT is used for log compression. The
LUT contains the 8-bit logarithm values of multiples of
4 (e.g., 4, 8, 12, …, 65 532) for the 16-bit envelop echo
data. Thus, the 14-bit address is used by truncating 2 bits
in the least significant bit of the input data. In addition,
downsampling is applied to reduce the data rate (e.g.,
1024 samples per scanline), and image enhancement (e.g.,
black-hole filter) and zone blending for multizone focusing
are also applied, as shown in Fig. 5.
3) Scan Conversion: In scan conversion, the ultrasound
data with polar coordinates are geometrically transformed
into the Cartesian raster display data. The addresses and
coefficients for bilinear interpolation in scan conversion
are computed in real time by using the coordinate rotation digital computer algorithm [23]. The scan-converted
raster pixel data are temporally stored in two synchronous dynamic RAM (SDRAMs) for display. In the portable system developed, these data are transferred into the
system controller (i.e., Samsung S3C6410) via external
DMA without a video processing unit to further reduce
the hardware resource.
D. CPU Module
In the portable ultrasound imaging system developed, a
Samsung S3C6410 mobile processor running at 667 MHz
is used. A Linux kernel is stored in a flash memory for
faster boot (<10 s). The portable system developed can
support various peripheral interfaces, e.g., local access
network (LAN), 16-gigabyte micro secure digital (SD),
and universal serial bus (USB) 1.1. In addition, the digital video interface (DVI) is provided to drive an external
monitor. The system parameters (mode, gain, TGC, and
dynamic range) can be adjusted by a user via a 10.2-inch
touch-screen LCD monitor.
The power module used in our prototype portable system provides all the regulated power from a built-in 4-cell
Li-ion battery, which can drive HV pulsers (i.e., maximum
± 70 V), analog circuits, and digital circuits. The battery is capable of providing 14.8 V with 2400 mAh. The
HV is generated by using a quasi-resonance circuit with
switching frequency of 65 kHz, transformer, and feedback
circuit. Therefore, the maximum regulated voltage is determined by the transformer turns ratio (e.g., 16:42) and
feedback circuit. The regulation circuit for HV is operated
in the intermittent mode for the various HV levels.
F. Experimental Setup
Simulation and phantom experiments were conducted
to evaluate the performance of the proposed efficient algorithms in the portable ultrasound imaging system developed. A simulation model was generated by the Field
II program [24]. In the simulation, an image of the point
targets located at different depths and speckle patterns
was obtained by using a 3.5-MHz convex array. The parameters used in the simulation are summarized in Table
I. As listed in Table I, to evaluate the EA technique, the
center 16-element array was first used for transmission
and reception. The next transmission was conducted on
the same scanline with the same center 16-element array,
whereas the neighboring 16-element array was used for reception. The beamforming was performed for each reception, and two sequentially beamformed data points were
accumulated to obtained one scanline. For the phantom
experiment, while a multipurpose tissue-mimicking phantom (Model 539, ATS Laboratories Inc., Bridgeport, CT)
was scanned with a 3.5-MHz convex array transducer, a
near-field tissue-mimicking phantom (Model 551, ATS
Laboratories Inc.) was scanned with a 7.5-MHz linear array transducer.
G. Evaluation Metrics
In the simulation, for quantitative evaluation, the −18dB lateral resolution was measured with a contour map
for a point target. In addition, the contrast-to-noise ratio
(CNR) was calculated by
CNR =
µc − µs
,
(σ c2 + σ s2)
(5)
where μs and μc are the average intensities in the speckle
and cyst regions, respectively, and σ s2 and σ c2 are the variances of each region.
III. Results and Discussion
A. Simulation Results
Fig. 6 shows the simulation results of an effective
32-channel system with 60-dB dynamic range from the
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IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control , vol. 59, no. 7, July 2012
TABLE I. Parameters Used for the Simulation.
Parameter
Value
Sampling frequency (MHz)
Number of channels
Number of scanlines
Center frequency (MHz)
Field of view (degree)
Radius of curvature (mm)
Element pitch (mm)
Element height (mm)
Elevation focus (mm)
Transmit focus (mm)
Dynamic range (dB)
40
16
192
3.5
85.256
40
0.31
13
80
50
60
conventional dynamic receive focusing and pseudo-dynamic focusing methods without receive apodization. In
this study, although, in the conventional dynamic receive
focusing, the focusing delay value in (3) is updated for every focusing point, it is shared for multiple focusing points
within the same focusing zone in the pseudo-dynamic focusing method. In addition, in the pseudo-dynamic focusing method, the number of shared focusing points at
each focal zone was dynamically adjusted depending on
imaging depth to minimize the focusing errors. In other
words, for the first 5-cm imaging depth, 32 focusing points
use the same focusing delay value, i.e., 32 shared focusing
points. In the next 5-cm imaging depth (i.e., 5 to 10 cm),
the same focusing delay value is applied for 64 focusing
points. In the simulation, for the imaging depth of 12 cm,
the focusing delay values used in the conventional dynamic receive focusing method were 6144 (12 × 512), whereas
those for the pseudo-dynamic focusing method were 128
(80 zones for 0 to 5 cm, 40 zones for 5 to 10 cm, and 8
zones for 10 to 12 cm). As shown in Figs. 6(a) and 6(b),
with visual assessment, it is difficult to find the impact of
using the different numbers of focusing delay values from
the dynamic and pseudo-dynamic receive focusing methods (i.e., 6144 versus 128, respectively).
For a quantitative comparison, the −18-dB lateral resolutions of point targets at each depth were measured and
are shown in Fig. 7. As illustrated in Fig. 7, the pseudo-dynamic receive focusing method yielded a negligible
degradation in lateral resolution (i.e., <0.2 mm). On the
other hand, when the Hanning window was used for the
apodization, the identical lateral resolution with broadened main lobe width was obtained at each depth from
both methods. Similar results were obtained in the CNR
for the region marked in Fig. 6(a) (i.e., 2.84 and 2.81 for
the dynamic and pseudo-dynamic receive focusing method, respectively). These results indicate that the proposed
pseudo-dynamic focusing method is sufficient for the current portable ultrasound imaging system. However, the
degradation of image quality from the pseudo-dynamic focusing would be more pronounced with the higher channel
ultrasound imaging system (e.g., 64 channels). Because
of the nonlinear increase in the focusing delay values, the
pseudo-dynamic focusing method will introduce a substantial number of delay errors, especially in the near field
[25]. Thus, for the higher channel ultrasound imaging system, the degradation in image quality can be reduced by
assigning the small number of shared focusing points in
the near field (e.g., 16, 64, and 128 shared focusing points
for imaging depths of 0 to 2 cm, 2 to 6 cm, and 6 to
12 cm, respectively).
B. Prototype Low-Cost Portable Ultrasound System
Fig. 8 shows a prototype of the low-cost portable ultrasound system developed. The system specifications
and parts of the portable ultrasound system developed
are summarized in Table II. As listed in Table II, the
prototype ultrasound system can support the B-mode and
BM-mode, and the size (245 mm width × 190 mm height)
and weight (about 560 g) are suitable for POC applications. For display, a 10.2-inch touch screen LCD monitor
is attached for displaying a B-mode image with single,
Fig. 6. Field II simulation images of an effective 32-channel system using (a) the conventional dynamic receive focusing method and (b) the
pseudo-dynamic receive focusing method.
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kim et al.: FPGA-based portable ultrasound imaging system
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Fig. 7. −18 dB lateral resolution from the Field II simulation at each
imaging depth for the dynamic and pseudo-dynamic receive focusing
methods.
dual, and quad screen formats. The dual and quad modes
can display two and four images, respectively, to allow
clinicians to evaluate multiple images side-by-side. In addition, the cine mode with 256 frames is available, and
the captured images can be directly exported via the USB
interface. The keyboard-type buttons are used for menu
navigation and the user text interface.
Figs. 9(a) and 9(b) show the main board and the power
supply module inside the prototype portable ultrasound
system developed. As shown in Fig. 9(a), the main board
consists of the ultrasound scanner module and the CPU
module with LAN, USB, micro SD, and DVI. In the ultrasound scanner module, there are eight HV multiplexers,
16 HV pulsers, eight pulser drivers, two ADC chips, and
a Spartan-3 FPGA chip. The connector at the top of the
main board is used for interconnecting between the main
board and the power module, whereas the left one connects the main board to the ultrasound probe. The power
module provides all the power required in analog and digital circuits, as shown in Fig. 9(b). Furthermore, the HV
(i.e., ± 70 V) is supplied for driving the HV pulser. The
voltage level in the HV pulser can be adjusted from the
Fig. 8. Prototype low-cost portable ultrasound system.
Spartan-3 FPGA for supporting various modes, e.g., Bmode, C-mode, and D-mode.
C. Demonstration of the Portable
Ultrasound Imaging System Developed
Figs. 10(a) and 10(b) show the captured images using a 3.5-MHz convex array transducer and a 7.5-MHz
linear array transducer with the developed prototype portable ultrasound system from two tissue-mimicking phantoms with imaging depths of 14 and 4 cm, respectively.
As shown in Fig. 10(a), with the 3.5-MHz convex array
probe, the portable system developed can clearly show
point targets up to 13 cm, and cystic lesions are also depicted. Similarly, the portable system developed clearly
visualized the point targets within 4 cm with the 7.5-MHz
linear array transducer. Further evaluation of the portable
TABLE II. System Specifications.
Mode
B-mode, BM-mode
Size
Weight
Power
Probe
Display
CPU
OS
System memory
FPGA
Peripherals
Display mode
Cine
245-mm width × 190-mm height
560 g
External power module/battery
3.5-MHz convex and 7.5-MHz linear array probes
10.2-inch TFT LCD (800 × 480) with touch panel
Samsung S3C6410 running at 667 MHz
Linux kernel 2.6.21
256 MB (SDRAM), 4 GB (flash)
Xilinx Spartan-3 (XC3S4000)
USB1.1 host and client, microSD, LAN, DVI for external monitor
Dual and quad B-mode
256 frames
LCD = liquid crystal display; OS = operating system; SDRAM = synchronous dynamic RAM; USB = universal
serial bus; DVI = digital visual interface.
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IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control , vol. 59, no. 7, July 2012
Fig. 9. (a) Ultrasound scanner and CPU modules and (b) power and
battery modules.
ultrasound imaging system developed will be conducted
for various POC applications (e.g., emergency medicine).
The hardware complexity of each processing module in
the portable system developed was analyzed by using the
ISE9.2 synthesis tool (Xilinx), and the results are summarized in Table III, along with a list of the equivalent
gate counts. Because of the proposed efficient beamforming algorithms (i.e., pseudo-dynamic receive focusing and
LUT-based delay update), the hardware complexity in the
front-end processing (i.e., beamforming) is comparable
with the mid and back-end B-mode processing, as listed
in Table III (2 612 565 versus 2 081 064 in equivalent gate
counts). When all processing modules listed in Table III
are embedded in the Spartan-3 FPGA chip, they use 46,
41, 93, and 86% of slide flip-flops, 4-input LUTs, block
RAMs, and multipliers. Thus, all the computational and
data transfer rate requirements for the low-cost portable
B-mode ultrasound imaging system can be handled by the
cost-effective single FPGA chip (<$50). Furthermore, the
portable system provides a battery lifetime of 1.5 h when
scanning continuously.
III. Conclusion
In this paper, we present a low-cost portable ultrasound imaging system based on a single FPGA for point-
Fig. 10. Phantom images by the prototype portable ultrasound imaging
system with (a) a 3.5-MHz convex array probe and (b) a 7.5-MHz linear
array probe.
of-care applications. The prototype of the portable ultrasound system developed showed that it can handle all the
ultrasound signal and image processing requirements in
real time. We believe the size (245 mm width × 190 mm
height) and weight (about 560 g) as well as the functionality of the portable system would be a good fit for investigating its clinical benefits in emerging POC applications
(e.g., emergency rooms and nursing care).
TABLE III. Hardware Complexity of Each Processing
Module in the Developed Low-Cost Portable
Ultrasound Imaging System
Processing module
Equivalent
gate count
Transmit and receive beamforming
Mid and back-end B-mode processing
Scan conversion
Real-time control and others
Total
2 612 565
2 081 064
153 696
1 806 177
6 653 502
The equivalent gate count was estimated by using the Xilinx ISE9.2
synthesis tool.
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kim et al.: FPGA-based portable ultrasound imaging system
References
[1]J. J. Hwang, J. Quistgaard, J. Souquet, and L. A. Crum, “Portable
ultrasound device for battle field trauma,” in Proc. IEEE Ultrason.
Symp., vol. 2, pp. 1663–1667, 1998.
[2] M. Karaman, P. C. Li, and M. O’Donnell, “Synthetic aperture imaging for small scale systems,” IEEE Trans. Ultrason. Ferroelectr. Freq.
Control, vol. 42, no. 3, pp. 429–442, 1995.
[3]Y. M. Yoo, F. K. Schneider, A. Agarwal, T. Fukuoka, L. M. Koh,
and Y. Kim, “Ultrasound machine for distributed diagnosis and
home use,” in Proc. 1st Distributed Diagnosis and Home Healthcare
Conf., 2006, pp. 63–66.
[4] P. N. T. Wells, “The prudent use of diagnostic ultrasound,” Ultrasound Med. Biol., vol. 13, no. 7, pp. 391–400, 1987.
[5] B. P. Nelson and K. Chason, “Use of ultrasound by emergency
medical services: A review,” Int. J. Emerg. Med., vol. 1, no. 4, pp.
253–259, 2008.
[6]J. J. Hwang and J. Quistgaard, “A portable ultrasound array imaging device,” Proc. SPIE, vol. 3664, pp. 194–201, 1999.
[7]S. Sikdar, R. Managuli, L. Gong, V. Shamdasani, T. Mitake, T.
Hayashi, and Y. Kim, “A single mediaprocessor-based programmable ultrasound system,” IEEE Trans. Inf. Technol. Biomed., vol. 7,
no. 1, pp. 64–70, 2003.
[8]Y. Kim, J. H. Kim, C. Basoglu, and T. C. Winter, “Programmable
ultrasound imaging using multimedia technologies: A next-generation ultrasound machine,” IEEE Trans. Inf. Technol. Biomed., vol.
1, no. 1, pp. 19–29, 1997.
[9] V. Shamdasani, R. Managuli, S. Sikdar, and Y. Kim, “Ultrasound
color-flow imaging on a programmable system,” IEEE Trans. Inf.
Technol. Biomed., vol. 8, no. 2, pp. 191–199, 2004.
[10]S. Sikdar, V. T. Shamdasani, M. S. Lidstrom, K. W. Beach, and Y.
Kim, “Low-cost detection and monitoring of coronary artery disease using ultrasound,” in Proc. 1st Distributed Diagnosis and Home
Healthcare Conf., 2006, pp. 55–58.
[11]Y. M. Yoo, R. Managuli, and Y. Kim, “New multi-volume rendering
technique for three-dimensional power Doppler imaging,” Ultrasonics, vol. 46, no. 4, pp. 313–322, 2007.
[12] U. Bae, M. Dighe, V. Shamdasani, S. Minoshima, T. Dubinsky,
and Y. Kim, “Thyroid elastography using carotid artery pulsation:
A feasibility study,” in Proc. IEEE Ultrasonics Symp., 2006, pp.
614–617.
[13]A. Agarwal, F. K. Schneider, Y. M. Yoo, and Y. Kim, “Image quality evaluation with a new phase rotation beamformer,” IEEE Trans.
Ultrason. Ferroelectr. Freq. Control, vol. 55, no. 9, pp. 1947–1955,
2008.
[14] F. K. Schneider, Y. M. Yoo, A. Agarwal, L. M. Koh, and Y. Kim,
“New demodulation filter in digital phase rotation beamforming,”
Ultrasonics, vol. 44, no. 3, pp. 265–271, 2006.
[15] F. K. Schneider, A. Agarwal, Y. M. Yoo, T. Fukuoka, and Y. Kim,
“A fully programmable computing architecture for medical ultrasound machines,” IEEE Trans. Inf. Technol. Biomed., vol. 14, no. 2,
pp. 538–540, 2010.
[16] B. G. Tomov and J. A. Jensen, “A new architecture for a single-chip
multi-channel beamformer based in a standard FPGA,” in Proc.
IEEE Ultrasonics Symp., 2001, pp. 1529–1533.
[17] B. G. Tomov and J. A. Jensen, “Compact FPGA-based beamformer
using oversampling 1-bit A/D converters,” IEEE Trans. Ultrason.
Ferroelectr. Freq. Control, vol. 52, no. 5, pp. 870–880, 2005.
[18] K. Ranganathan, M. Santy, T. N. Blalock, J. A. Hossack, and W.
F. Walker, “Direct sampled I/Q beamforming for compact and very
low-cost ultrasound imaging,” IEEE Trans. Ultrason. Ferroelectr.
Freq. Control, vol. 51, no. 9, pp. 1082–1094, 2004.
[19] H. H. Han, J. J. Kim, and T.-K. Song, “Hardware-efficient methods
for eliminating of signal distortion in sigma-delta based ultrasound
beamformer,” Ultrason. Imaging, vol. 31, no. 2, pp. 101–119, 2009.
[20]A. Agarwal, Y. Yoo, F. K. Schneider, C. Gao, L. M. Koh, and Y.
Kim, “New demodulation method for efficient phase rotation beamforming,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 54,
no. 8, pp. 1656–1668, 2007.
[21]C. Yoon, J. Lee, Y. Yoo, and T.-K. Song, “Display pixel based focusing using multi-order sampling for medical ultrasound imaging,”
Electron. Lett., vol. 45, no. 25, pp. 1292–1294, 2009.
[22]S. Stergiopoulos, Advanced Signal Processing Handbook: Theory and
Implementation for Radar, Sonar, and Medical Imaging Real Time
Systems. Boca Raton, FL: CRC Press, 2000.
1393
[23]J. E. Volder, “The CORDIC trigonometric computing technique,”
IRE Trans. Electron. Comput., vol. EC-8, no. 3, pp. 330–334, 1959.
[24]J. A. Jensen, “FIELD: A program for simulating ultrasound systems,” Med. Biol. Eng. Comput., vol. 34, suppl. 1, pt. 1, pp. 351–353,
1996.
[25] H.-Y. Sohn, J. Kang, J. Cho, T.-K. Song, and Y. Yoo, “Timesharing bilinear delay interpolation for ultrasound dynamic receive
beamformer,” Electron. Lett., vol. 47, no. 2, pp. 89–91, 2011.
Gi-Duck Kim was born in Incheon, Korea, in
1975. He received the M.S. and Ph.D. degrees in
the Department of Electronic Engineering from
Sogang University, Seoul, Korea, in 2000 and
2008, respectively. From 1999 to 2003, he conducted research and development in ultrasound echo
processing at Medison, Seoul, Korea, and from
2008 to 2010, he was a systems engineer for ultrasound systems at Bionet, Seoul, Korea. He is currently a research professor of Sogang Institute of
Advanced Technology (SIAT) in Sogang University, Seoul, Korea. His research interests include signal processing and
low-cost system design for handheld ultrasound systems.
Changhan Yoon received the Bachelor and
Master of Science degrees in electronic engineering
in 2007 and 2009 from Sogang University, Seoul,
Korea. He is currently pursuing a Ph.D. degree in
the Department of Electronic Engineering at Sogang University. His main research interests include medical ultrasound imaging and therapy,
portable ultrasound imaging systems, digital signal processing, digital system design, and photoacoustic imaging.
Sang-Bum Kye was born in Seoul, Republic of
Korea, in 1966. He received his B.S. degree in electrical engineering from Korea University in 1989,
and the M.S degree in electrical and electronic
engineering from Korea Advanced Institute of Science and Technology in 1992. From 1992 to 2007,
he conducted research and development on ultrasound scanners at Medison Co. Ltd., and from
2007 to 2010 at Bionet Co. Ltd. He is currently
pursuing a Ph.D. degree in the Department of
Electronic Engineering at Sogang University,
Seoul, Korea. His research interests include signal processing and lowcost system design of ultrasound systems for point of care.
Youngbae Lee was born in Seoul, Republic of
Korea, in 1965. He received the B.S. degree in
electrical engineering from Yonsei University in
1990 and the M.S. degree in electrical and electronic engineering from Korea Advanced Institute
of Science and Technology in 1992. He conducted
research and development on medical ultrasound
scanners from 1992 to 2002 at Medison Co. Ltd.,
from 2003 to 2007 at the Siemens Ultrasound
Group Korea, and from 2008 to 2010 at Bionet
Co. Ltd. He is currently pursuing a Ph.D. degree
in the Department of Electronic Engineering at Sogang University, Seoul,
Korea. His research interests include signal processing and ultrasound
scanners for point of care.
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1394
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control , vol. 59, no. 7, July 2012
Jeeun Kang received the Bachelor degree in
electronic engineering in 2009 from Sogang University, Seoul, Korea. He is currently a candidate
for the Master degree in electronic engineering at
Sogang University. His main research interests are
focused on implementation of a portable ultrasound system, and imaging algorithms of ultrasound and photoacoustic imaging.
Yangmo Yoo received the B.S. and M.S. degrees
in electronics engineering in 1999 and 2001, respectively, from Sogang University, Seoul, Korea,
and the Ph.D. degree in bioengineering in 2007
from the University of Washington, Seattle. From
2007 to 2009, he was a systems design engineer
with Philips Healthcare, Bothell, WA. He is currently an assistant professor of electronics engineering and is in the Interdisciplinary Program of
Integrated Biotechnology at Sogang University.
His research interests include medical ultrasound
imaging and its clinical applications in diagnostics
and therapy.
Tai-Kyong Song (M’97) received his B.S. degree
in electronic engineering from Sogang University,
Seoul, Korea, in 1984, and his M.S. and Ph.D.
degrees in the Department of Electrical and Electronic Engineering from the Korea Advanced Institute of Science and Technology (KAIST), Seoul,
Korea, in 1985 and 1990, respectively. He worked
in the department of Physiology and Biophysics,
Mayo Clinic, Rochester, MN, as a research fellow
for 2 years before being appointed as an adjunct
professor in the Department of Information and
Communication Engineering at KAIST from 1993 through 1995. He
worked at Siemens Medical-System Inc., Issaquah, WA, as a staff scientist from 1995 through 1997 and joined the Department of Electronic
Engineering at Sogang University, Seoul, Korea, as an assistant professor
in 1997. He was promoted to professor in 2006.
Dr. Song has been the director of the Center for Medical Solution
Research at Sogang University since 1997. He served as an associate editor of IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency
Control from 2002 through 2007. He is currently the vice president for
research, dean of the Industry–University Cooperation Foundation, and
the vice director of the Sogang Institute of Advanced Technology at
Sogang University.
His research interests include handheld ultrasound imaging systems,
real-time 3-D scanning algorithm and system development, high-end
digital ultrasound imaging systems, and ultrasound signal and imaging
processing.
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