ieee transactions on ultrasonics, ferroelectrics, and frequency control, vol. 51, no. 1, january 2004

93

Detection of Lumen-Intima Interface ofPosterior Wall for Measurement of Elasticity of
the Human Carotid Artery
Hideyuki Hasegawa, Member, IEEE, Hiroshi Kanai, Member, IEEE, and Yoshiro Koiwa
Abstract—In our series of studies on noninvasive assessment of the regional elasticity of the arterial wall, the displacement gradient (change in thickness) of the arterial
wall caused by the heartbeat was measured by the phasedtracking method. Because the displacement gradient corresponds to the strain due to the change in blood pressure, theelasticity can be evaluated from the displacement gradientof the arterial wall and the blood pressure, which are noninvasively measured at the upper arm. In the measurement of
the elasticity of the arterial wall by our method, the regionin which the elastic modulus is estimated must be assigned
beforehand; currently, the lumen-intima boundary of thearterial wall is manually determined by the operator. For
the real-time measurement of the elasticity of the arterial
wall, a fast, automated method is necessary for detection of
the boundary. In this paper, a cost function is proposed for
diﬀerentiation of the arterial wall from the lumen. The proposed cost function was applied to ultrasound data, whichwere noninvasively obtained for ﬁve human carotid arteries. In comparison with the case of detection using only the
amplitude of the echo, the root mean square error between
the automatically detected lumen-intima boundary and themanually assigned boundary was signiﬁcantly improved byusing the proposed cost function. Furthermore, the lumenintima boundary was automatically detected in a short period. Such a method is required for real-time measurementof the elasticity of the arterial wall, though detection of theouter boundary of the adventitia, which is not described inthis paper, is also necessary to realize real-time elasticity
measurement by our method.

I. Introduction
he steady increase in the number of patients withmyocardial infarction or cerebral infarction, both ofwhich are considered to be mainly caused by atherosclerosis, is becoming a serious problem [1], [2]. Therefore, it
is important to diagnose atherosclerosis in the early stage.
Computed tomography (CT), magnetic resonance imaging(MRI), and ultrasonic diagnostic equipment are used forthe diagnosis of atherosclerosis [3]–[5]. However, they provide information only on the shape of the artery, such as
the diameter of the lumen. In addition, CT and MRI are
not suitable for repetitive diagnosis due to the exposure
to radiation and the high expense. However, the diameterof the lumen, which can be measured by these methods, is
not changed by early-stage atherosclerosis [6].

T

Manuscript received September 19, 2002; accepted July 31, 2003.
H. Hasegawa and H. Kanai are with the Graduate School ofEngineering, Tohoku University, Sendai 980-8579, Japan (e-mail:hasegawa@us.ecei.tohoku.ac.jp).
Y. Koiwa is with the Graduate School of Medicine, Tohoku University, Sendai 980-8575, Japan.

Because there are signiﬁcant diﬀerences between theelastic moduli of the normal arterial walls and those affected by atherosclerosis [7], [8], evaluation of the elasticity of the arterial wall is useful for diagnosis of early-stage
atherosclerosis [9]. In addition to diagnosis of early-stage
atherosclerosis, it also is important to diagnose vulnerability of atherosclerotic plaque because the rupture of suchplaque causes acute myocardial infarction and cerebral
infarction [10]–[12]. Evaluation of mechanical properties,
such as elasticity of atherosclerotic plaque, is useful forthe diagnosis of vulnerability of such plaque. Using standard ultrasonic diagnostic equipment, intima-media thickness (IMT) can be evaluated noninvasively [5]. However,
the mechanical properties of atherosclerotic plaque cannot
be determined.
To measure the elasticity of the arterial wall, the pulse
wave velocity (PWV) method has been developed as atechnique for the noninvasive diagnosis of atherosclerosis[13]. In this method, the elasticity of the arterial wall isevaluated by measuring the velocity of the pressure wave
propagating from the heart to the femoral artery. Though
it is useful in terms of noninvasive evaluation of the elasticity, regional elasticity cannot be evaluated due to a low
spatial resolution of tens of centimeters, which almost corresponds to the distance from the heart to the femoral
artery.
To improve the spatial resolution in measurement of
PWV, we previously proposed a method to accurately
measure the propagation velocity of vibrations on the arterial wall using ultrasound [14]–[16]. Using this method,
the PWV between two adjacent points, which are separated from each other by several centimeters, can be noninvasively measured by estimating the time delay between
the resultant vibrations at these two points set along theaxial direction of the artery.
Methods for measurement of the change in artery diameter have been proposed [17]–[21] in order to obtain the circumferential distensibility of the arterial wall in the planethat is perpendicular to the axial direction of the artery.
By assuming the artery to be a cylindrical shell, the average elasticity of the entire circumference of the plane canbe evaluated [22]–[24]. However, the regional elasticity ofatherosclerotic plaque cannot be obtained by these methods because an artery with such plaque cannot be assumed
to be a cylindrical shell with uniform wall thickness.
Recently, Bonnefous [25] measured the displacement
and strain around carotid atherosclerotic plaque using tis-c 2004 IEEE
0885–3010/$20.00 94ieee transactions on ultrasonics, ferroelectrics, and frequency control, vol. 51, no. 1, january 2004

sue Doppler imaging. He showed the inhomogeneity of thedisplacement upstream and downstream of atherosclerotic
plaque and suggested that the arterial wall motion has
potential for evaluation of plaque vulnerability.
De Korte et al. [26] and Céspedes et al. [27] evaluatedthe elasticity of coronary atherosclerotic plaque using intravascular ultrasonography (IVUS). They compared themeasured elasticity distribution with the pathological image and showed that it was possible to characterize tissues
in atherosclerotic plaque by measuring its elasticity.
In our series of studies, we have been attempting toevaluate the elasticity of a local region, even in the caseof atherosclerotic plaque using transcutaneous ultrasound.
Such a technique for measurement of the spatial distribution of the regional elasticity would be useful for diagnosisof the vulnerability of such plaque as well as for the diagnosis of early-stage atherosclerosis. In our method, thesmall displacement gradient (change in thickness) of thearterial wall due to the heartbeat was accurately measured
in each local region that corresponds to the focal area ofthe ultrasonic beam [15], [28]–[30]. From the resultant displacement gradient, the regional strain and the elasticityof the arterial wall were noninvasively evaluated [31], [32].
In the measurement of the elasticity of the arterial wallby our method, the region in which the elastic modulus isestimated must be assigned; currently, the lumen-intima
boundary of the arterial wall is manually determined by
an operator. For the real-time measurement of the elasticity of the arterial wall, an automated method for detectionof the boundary of the arterial wall in a short time is indispensable.
In the literature, several methods have been proposedfor detection of the arterial wall boundary using the ultrasound B-mode image. For measurement of the ﬂowmediated dilation response [33], methods for detection of
the boundary of the arterial wall have been proposed formeasurement of the arterial diameter [34]–[37]. Fan et al.
[34] used an adaptive template, which approximated theenvelopes of echoes reﬂected by the lumen-intima interface and media-adventitia interface. Stadler et al. [35] estimated the arterial diameter from the B-mode image ofthe artery that was obtained by rotating the scan planeslightly oﬀ of the vessel axis. Under such conditions, thecross section of the artery can be modeled as an ellipse,
and the arterial diameter is obtained by estimating thesize of the ellipse. Beux et al. [36] used the gradient of
the intensity in the B-mode image of the artery. Neweyand Nassiri [37] estimated the arterial diameter from the
B-mode image using the neural network. In these methods
for measurement of the ﬂow-mediated dilation response,the media-adventitia boundary was used for measurementof the arterial diameter, and the lumen-intima boundary
was not used because the amplitude of the echo reﬂectedby the media-adventitia interface is usually high and stablein comparison with that from the lumen-intima interface.
However, the lumen-intima boundary must be determined
for measurement of the arterial elasticity in our method.

For measurement of the IMT, several methods havebeen proposed for detection of the lumen-intima boundary using the ultrasound B-mode image [38], [39]. In thesemethods, the lumen-intima boundary is precisely detectedusing dynamic programming [38] and the active surface
technique [39]. However, such sophisticated methods aretime consuming and, therefore, not suitable for the realtime measurement of the elasticity of the arterial wall.
Hoeks et al. [40] and Willekes et al. [41] proposed a methodfor detection of the IMT using the time averaged envelope of the echo. In this method, the envelope of the echo
is averaged with compensation of the motion of the arterial wall using the wall tracking method [19]. However,displacement of each sampled point along the ultrasonicbeam must be estimated before detection of the lumenintima boundary in order to compensate for the motion of
the arterial wall.
In this paper, a new method is proposed for detectionof the lumen-intima boundary of the posterior wall of thehuman carotid artery during a suﬃciently short period.
Such a method is necessary for real-time measurement of
the elasticity of the arterial wall. However, this method is
not suﬃcient to realize the real-time elasticity measurement by our method because the luminal boundary of theanterior wall and the outer boundary of adventitia also areneeded.
II. Methods
A. Oﬀ-Line and Manual Processing of Ultrasonic Data
for Assessment of Arterial Wall Elasticity
In this section, an example of oﬀ-line and manual processing of ultrasonic data for assessment of arterial wall
elasticity is shown to illustrate the need for automaticboundary detection.
For measurement of the elasticity of the arterial wall,the displacement of an object is estimated using thequadrature demodulated signal of the received ultrasonicwave. A quadrature demodulated signal is obtained using
a 7.5 MHz linear-type ultrasonic probe of ultrasonic diagnostic equipment (Toshiba SSH-140A, Toshiba Corporation, Tokyo, Japan). Because ultrasonic beams are scanned
at 60 positions along the axial direction of the artery,with spacing of 300 µm at a pulse repetition frequencyof 12 kHz, the frame rate becomes 12 kHz/60 = 200 Hz.
The in-phase and quadrature signals are simultaneously
A/D converted with a 12-bit A/D converter at a sampling
frequency of 10 MHz.
From the acquired demodulated signal, z(t; d; ), reﬂected at a time, t, at a depth, d, at a beam position,
, the elasticity of each local region in the arterial wall are
obtained as follows.
1. Manual Assignment of Initial Depths of LumenIntima Boundary and Outer Boundary of Adventitia: The
lumen-intima boundary and the outer boundary of adventitia must be assigned manually with respect to the pos-hasegawa et al.: method for detection of lumen-intima boundary of carotid artery

95

Fig. 1. Procedure for measuring the elasticity of the arterial wall. (a) B-mode image of carotid artery of a 29-year-old male obtained bystandard ultrasonic diagnostic equipment. (b) Manually assigned the lumen-intima boundary (LIB) and the outer boundary of adventitia(OBA) superimposed on the B-mode image reconstructed from the quadrature demodulated signal. (c) Electrocardiogram. (d) Displacement,
xi−2 (t; ), of (i − 2)-th point. (e) Displacement, xi+2 (t; ), of (i + 2)-th point. (f) Displacement gradient (Change in thickness), ∆hi (t; ), of
i-th layer. (g) Elasticity image.

terior wall to specify where the arterial wall is. This isdone by manually tracing the B-mode image at time t0 of
the R-wave of the electrocardiogram reconstructed fromthe acquired quadrature demodulated signal as shown in
Fig. 1(b). In Fig. 1, a data set, measured at the carotid
artery of 29-year-old male, is shown as an example of elasticity measurement.
In some cases, the lumen-intima boundary of the anterior wall cannot be clearly recognized in the B-mode image due to the inﬂuence of the multiple reﬂection from theanterior wall and scattering from the tissue between theanterior wall and the skin surface. Therefore, we focus ourattention on the posterior wall in the measurement of thearterial wall elasticity.

the -th ultrasonic beam, the displacement of each point,xi (t; )(i = 1, 2, . . . , N ), is estimated using the phasedtracking method [14]. For estimation of the displacement,
the phase shift, ∆ψi (t; ), between two consecutive echoes
is obtained from the complex cross-correlation function
calculated for Mc + 1 samples in the depth direction asshown in (1) (see next page), where D and Tr are the interval of sampled points in the depth direction and thepulse repetition interval, respectively, and ∗ represents thecomplex conjugate. In (1), Mc + 1 is set at 5 (= 0.4 µs) in
consideration of the pulse length of 0.46 µs. In estimationof the phase shift by (1), the object position is tracked byintegrating the average velocity, vi (t + Tr /2; ), during thepulse repetition interval, Tr , as follows:

2. Estimation by the Phased Tracking Method of the
Displacement Gradient (Change in Thickness) of the Arterial Wall Due to the Beating of the Heart: With respect
to N sampled points between the assigned lumen-intima
boundary and the outer boundary of adventitia alongTrxi (t + Tr ; ) = xi (t; ) + vi t + ;  × Tr2c0
= xi (t; ) +∆ψi (t), (xi (t0 ; ) = 0), (2)
2ω0

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ieee transactions on ultrasonics, ferroelectrics, and frequency control, vol. 51, no. 1, january 2004



Mc /2

z(t + Tr ; d + xi (t; ) + mD; ) · z ∗ (t; d + xi (t; ) + mD; )c,ej∆ψi (t;) = 

Mc /2



∗

z(t + Tr ; d + xi (t; ) + mD; ) · z (t; d + xi (t; ) + mD; )
m=−Mc /2

m=−M /2

where ω0 and c0 are the center angular frequency of theultrasonic pulse and the speed of sound, respectively.
From the estimated displacement, xi (t; ), shown in
Figs. 1(d) and (e), the displacement gradient (change
in thickness) of the arterial wall due to the heartbeat
is obtained. Because the spatial resolution of the ultrasound used is determined by the pulse length of 0.46 µs(= 354 µm at a speed of sound of 1540 m/s), the displacement gradient (change in thickness), ∆hi (t; ), of eachlayer with a constant thickness of h0 = 385 µm shown in
Fig. 1(f) is obtained as follows:∆hi (t; ) = xi−2 (t; ) − xi+2 (t; ),(i = 3, 4, . . . , N − 2). (3)3. Reconstruction of the Elasticity Image: From the ratio of the maximum decrease in thickness during one heartbeat, ∆hi,max () = maxt |∆hi (t; )|, to the initial thickness, h0 , of the i-th layer, the maximum strain of the i-th
layer is obtained by ∆εi,max () = ∆hi,max ()/h0 . Because
the deformation is suﬃciently small and is in the linear
regime, it shows incremental strain in the radial direction.
By assuming that the arterial wall is incompressible andthat the blood pressure is applied normal to each layer,
the elastic modulus, Eθ,i (), of the i-th layer along the-th beam is approximately given by [32]:
1 ρi0 ()N − i + 1∆pEθ,i () =+,2 h0 · NN
∆εi,max ()(4)where ρi0 () and ∆p are the initial inner radius of curvature of the i-th layer along the -th beam at a time
t0 and the pulse pressure (diﬀerence between the systolicblood pressure and the diastolic blood pressure) measured
at the upper arm, respectively. In (4), Eθ,i () represents
the circumferential elastic modulus. Thus, a subscript θ
indicates the circumferential direction of the artery. We
assumed that the pressure in the arterial wall decreases
linearly with the distance from the intimal side to the adventitia and that the arterial wall is almost isotropic. To
determine ρi0 (), the luminal boundary of the anterior wall
also is assigned manually by tracing the B-mode image ata time t0 .
For the region with a length of 18 mm along the axisof the artery, the regional elasticity, Eθ,i (), is estimatedon the cross-sectional image. Because the reﬂected ultrasound is received at a sampling frequency of 10 MHz after
quadrature demodulation, Eθ,i () is estimated at intervals(1)of 77 µm in the depth direction by shifting the initial depthof each layer by one sampled point. By scanning the ultrasound beam, Eθ,i () is obtained at intervals of 300 µm in
the axial direction of the artery, these intervals are determined by the spacing of the ultrasound beam. From theestimated Eθ,i () at intervals of 77 µm in the depth direction and 300 µm along the axis of the artery, the image ofregional elasticity is obtained as shown in Fig. 1(g).
As described above, three boundaries—the lumenintima boundaries of the posterior and anterior walls andthe outer boundary of adventitia of the posterior wall—
must be determined for measurement of the elasticity ofthe posterior wall by our method. In this paper, a method
is proposed for automatic detection of the lumen-intima
boundary of the posterior wall as a ﬁrst step for automatic
processing.
B. Cost Function for Diﬀerentiation of the Arterial Wallfrom the Lumen
1. Rationale for the Formulation of the Cost Function:
In order to take motions of the arterial wall and blood
particles, which cause the phase shift of the received ultrasonic wave, into account in this paper the lumen-intima
boundary of the arterial wall is automatically determinedusing the quadrature demodulated signal, z(t; d; ), which
is obtained at a time, t, a depth, d, and an ultrasonicbeam position, . Fig. 2(a) shows the B-mode image of the
carotid artery of a 50-year-old male obtained by standard
ultrasonic diagnostic equipment. The quadrature demodulated signal, z(t; d; ), with respect to the preset regionof-interest (ROI) shown in Fig. 2(a) was acquired, and the
B-mode image, which is reconstructed from the amplitude,|z(t0 ; d; )|, at time t0 of the R-wave of the electrocardiogram, is shown in Fig. 2(b). In Fig. 2(b), there are 192 (indepth) × 60 (in lateral) = 11520 points within the ROI.
In this paper, we search for the lumen-intima boundary of
the posterior wall from the center to the end of the ROI
by assuming that the center of the ROI corresponds to thelumen.
Fig. 3 shows the amplitude, |z(t0 ; d; 1 )|, of the quadrature demodulated signal measured at beam position 1 asshown in Fig. 2(b). In Fig. 3, the amplitude, |z(t0 ; d; )|, ofthe quadrature demodulated signal is plotted as a functionof depth, d. In position 1 , the amplitude, |z(t0 ; d; 1 )|, atthe lumen is not small. This is thought to be due to multiple reﬂection from the anterior wall or scattering fromthe tissue between the skin surface and the anterior wall.

hasegawa et al.: method for detection of lumen-intima boundary of carotid artery

97

Fig. 4. (a) Displacement at each depth at beam position 1 measured
by the phased-tracking method. (b) Displacement gradient at each
depth at beam position 1 .

Fig. 2. (a) B-mode image of the human carotid artery of a 50-year-old
male obtained by standard ultrasonic diagnostic equipment. (b) Bmode image within the ROI, which is reconstructed from the amplitude, |z(t; d; )|, of the quadrature demodulated signal. Amplitude,|z(t; d; )|, at position 1 is plotted as a function of depth in Fig. 3,
and displacements of points A, B, C, D, and E are shown in Fig. 4(a).

Fig. 3. Amplitude, |z(t0 ; d; )|, of the quadrature demodulated signal
obtained at time t0 of R-wave of the electrocardiogram at beam
position 1 shown in Fig. 2(b).

In the case of position 1 , when the lumen-intima boundary of the posterior wall is detected only from the amplitude, |z(t0 ; d; 1 )|, of the quadrature demodulated signal, it is diﬃcult to determine the optimal threshold level
for the amplitude because the echo at the lumen-intima
interface (at depth d2 , which is the manually assigned
lumen-intima boundary) cannot be discriminated from theecho in the lumen (at depth d1 ) only from the amplitude(|z(t0 ; d2 ; 1 )|/|z(t0 ; d1 ; 1 )| = 1.0). Therefore, it is diﬃcult
to detect the lumen-intima boundary only from the amplitude, |z(t; d; )|, of the echo.
Fig. 4(a) shows the displacement at each depth along
beam position 1 measured by the phased-tracking method
for the same subject as shown in Fig. 2. The displacement
at each depth is estimated by the phased-tracking method[14] described in Section II-A. In Fig. 4(a), the amplitude,|z(t0 ; d; )|, at the timing of the R-wave on the electrocardiogram is plotted in the right-hand side of Fig. 4(a).
Points D and E in Fig. 4(a) correspond to the lumen-intima
boundary and media-adventitia boundary of the posteriorwall, respectively. The IMT was measured as being 0.6 mm
from the B-mode image. Displacements were obtained ateach depth with an interval of 600 µm, which is equivalent to the IMT. The arterial wall has displacement due
to the change in blood pressure caused by the heartbeat.
The displacement in the lumen at position 1 shows motion toward the skin surface at the time when the innerpressure increases. Such estimated motion is considered tobe caused by the inﬂuence of the multiple reﬂection fromthe anterior wall or by scattering from the tissue between

98ieee transactions on ultrasonics, ferroelectrics, and frequency control, vol. 51, no. 1, january 2004

the skin surface and the anterior wall, because they movetoward the skin surface due to expansion of the artery.
Fig. 4(b) shows the displacement gradient at each depth
obtained by subtracting displacements at the two neighboring points shown in Fig. 4(b). Using the displacement
gradient, the diﬀerence between the arterial wall and lumen becomes larger in comparison with the displacement.
Thus, the displacement gradient has potential to be eﬀective for diﬀerentiation of the arterial wall from the lumen.
2. Formulation of the Cost Function: In this paper, we
propose using the cost function, which reﬂects the diﬀerence in the displacement gradient as well as the diﬀerencein the amplitude of the reﬂected ultrasonic wave, for diﬀerentiation of the arterial wall from the lumen as follows. A
complex signal, β(t; d; d12 ; ), which represents the phase
diﬀerence between two points at depths d and d+d12 along
an ultrasonic beam, , is deﬁned by:∗β(t; d; d12 ; ) = z (t; d; ) · z(t; d + d12 ; ),(5)where ∗ denotes the complex conjugate. Due to the motion of the arterial wall and the blood ﬂow in the lumen,β(t; d; d12 ; ) at a time, t0 , of the R-wave is diﬀerent fromthat after a time interval, T . Thus, the following is used asa model to estimate β(t0 +T ; d; d12 ; ) using β(t0 ; d; d12 ; ): 0 + T ; d; d12 ; ) = β(t0 ; d; d12 ; ) · γ(d; ),
β(t

(6)

where γ(d; ) is a complex parameter of the model that
corresponds to the changes in the amplitude and phase ofβ(t; d; d12 ; ) from β(t0 ; d; d12 ; ) to β(t0 + T ; d; d12 ; ), andthe phase, ∠γ(d; ), of γ(d; ) corresponds to the change indistance from d12 .
Let us deﬁne the mean squared diﬀerence, α(γ; d; ), 0 +between β(t0 + T ; d; d12 ; ) and its estimate, β(tT ; d; d12 ; ), as follows:α (γ; d; ) =1
(M + 1)(N + 1)



M/2

2

(M + 1)(N + 1) · α(γ; d; ) = A(d; ) + B(d; ) · |γ(d; )|− C(d; ) · γ ∗ (d; ) − C ∗ (d; ) · γ(d; ),(8)where A(d; ) and B(d; ) are real constants deﬁned by:


N/2





N/2

M/2

A(d; ) =2|β(t0 +T ; d+mD; d12 ; +nL)| ,(9)m=−M/2 n=−N/2M/2

B(d; ) =|β(t0 ; d+mD; d12 ; +nL)|2,(10)

m=−M/2 n=−N/2

and C(d; ) is a complex constant deﬁned by:

M/2C(d; ) =N/2β ∗ (t0 ; d + mD; d12 ;  + nL) ·m=−M/2 n=−N/2β(t0 + T ; d + mD; d12 ;  + nL). (11)By describing C(d; ) and γ(d; ) by the sum of their realand imaginary parts, Cr +jCi and γr +jγi , respectively, themean squared diﬀerence, α(γ; d; ), in (8) is described by:(M + 1)(N + 1) · α(γ; d; ) =A(d; ) + B(d; ) · γr2 + γi2 − 2 (Cr γr + Ci γi ) . (12)
By taking partial derivatives of α(γ; d; ) with respect
to γr and γi :1∂α
= Bγr − Cr ,(M + 1)(N + 1) ·
2
∂γr
1
∂α
= Bγi − Ci .
(M + 1)(N + 1) ·
2
∂γi



N/2

m=−M/2 n=−N/2β(t0 + T ; d + mD; d12 ;  + nL)2− β(t0 ; d + mD; d12 ;  + nL) · γ(d; ) ,β(t; d; d12 ; ) changes dependent on the displacement anddeformation of the object. Therefore, β(t0 + T ; d; d12 ; )has components that cannot be estimated by the model
deﬁned by (6) when the object has displacement and deformation. If the object has no displacement and deformation, β(t0 + T ; d; d12 ; ) can be perfectly estimated fromβ(t0 ; d; d12 ; ), and α(γ; d; ) will be minimized to zero.
Eq. (7) can be rewritten as:(7)

where D is the spacing (= 77 µm at a sound speed of
1540 m/s) between the succeeding sampled points in thedepth direction. By considering the lateral continuity of
the inner surface of the arterial wall in (7), α(γ; d; ) is averaged within N + 1 ultrasonic beams, which are scannedwith a spacing of L (= 300 µm). By increasing the number of ultrasonic beams to be averaged, the lateral continuity of the estimated lumen-intima boundary improves.
However, a nonsmooth boundary, such as atherosclerotic
plaque, cannot be detected when α(γ; d; ) is averaged by alarge number of ultrasonic beams. Therefore, in this paper,
minimum lateral averaging (N = 2) is used.
The α(γ; d; ) shows the squared diﬀerence betweenβ(t0 + T ; d; d12 ; ) and its estimate deﬁned by (6). The

(13)
(14)

In order to determine the complex variable γ (d; ),which achieves the minimum of α(γ; d; ), by setting theright-hand sides of (13) and (14) to zero as shown in (15)(see next page).
By substituting γ (d; ) of (15) into (8), the minimum
value, αmin (d; ), of α(γ; d; ) is given by (16) (see nextpage).
The value of αmin (d; ) increases when the change in
the amplitude, the displacement, and the displacement
gradient are large. If there is no change in the signal,β(t; d; d12 ; ), (i.e., there is no displacement and change inthickness, and the amplitude of β(t; d; d12 ; ) is constant.),
αmin (d; ) becomes zero. In this paper, αmin (d; ) is used
as a cost function, fcost (d; ), for detection of the lumenintima boundary:
fcost (d; ) = αmin (d; ).

(17)hasegawa et al.: method for detection of lumen-intima boundary of carotid arteryγ (d; ) ==C(d; )
B
M/2




99

N/2

β ∗ (t0 ; d + mD; d12 ;  + nL) · β(t0 + T ; d + mD; d12 ;  + nL)

m=−M/2 n=−N/2



M/2



(15)
.

N/2

|β(t0 ; d + mD; d12 ;  + nL)|2m=−M/2 n=−N/2αmin (d; )= min α(γ; d; )γ1=(M + 1)(N + 1)=|C(d; )|2A(d; ) −B(d; )

N/2
M/2


1
2
|β(t0 + T ; d + mD; d12 ;  + nL)|
(M + 1)(N + 1)
m=−M/2 n=−N/2

2
 M/2

N/2

 

∗


β
(t
;
d
+
mD;
d
;

+
nL)
·
β(t
+
T
;
d
+
mD;
d
;

+
nL)
0
12
0
12


m=−M/2 n=−N/2

−
.
N/2
M/2


2
(M + 1)(N + 1) ·|β(t0 ; d + mD; d12 ;  + nL)|(16)

m=−M/2 n=−N/2

The distance, d12 , between two points is set at 616 µm(at a sound speed of 1540 m/s), which is larger than thepulse length of 0.46 µs (= 354 µm at a sound speed of
1540 m/s), and the cost function, fcost (d; ), is averaged
within the pulse length (M = 4) in order to suppress therandom signal.
Because the squared diﬀerence, αmin (d; ), is used as thecost function, fcost (d; ), the cost function depends on thechange in β(t; d; d12 ; ) between t0 and t0 + T . Due to theﬁnite pulse length of 354 µm, the change in β(t; d; d12 ; )
becomes large when the displacement or the displacement
gradient becomes comparable to the pulse length. Therefore, the cost function, fcost (d; ), becomes large at thelumen-intima boundary because the displacement and displacement gradient are comparable to the pulse length asshown in Fig. 4. However, in the lumen, fcost (d; ) becomes
small because the displacement and displacement gradient
are small. Thus, the proposed fcost (d; ) is useful for differentiation of the arterial wall from the lumen.
In (16), t0 and T are set at the time of the R-wave
and 500 ms, respectively, to take the diﬀerence between
motions of the arterial wall and blood particles into account. After about 500 ms from the R-wave of the electrocardiogram [the time is shown by the vertical dashedline in Fig. 4(a)], the artery is expanded due to an increment in the blood pressure, and the blood particles,
which are inside the ultrasonic beam at time t0 of the
R-wave, are expelled by the blood ﬂow. Typically, sys-

tole lasts for about 300 ms, during which the displacement and the displacement gradient become maximum.
Although larger displacement is desirable to increase thecost function, the position of the peak in the cost function around the posterior wall becomes more dependent
on the wall displacement than that of the lumen-intima
boundary at the time of the R-wave. Because the position of lumen-intima boundary at the time of the R-waveof the electrocardiogram must be determined for elasticity
measurement as described in Section II-A, the maximum
displacement during systole is too large to determine thelumen-intima boundary at the time of the R-wave. Therefore, in this paper, T is set so as to be longer than systole.
In Fig. 5(a), the cost function, fcost (d; 1 ), which is obtained at the beam position 1 as shown in Fig. 2(b),is plotted by diamonds. By using fcost (d; ) the diﬀerence between the arterial wall and lumen becomes larger(fcost (d2 ; 1 )/fcost (d1 ; 1 ) = 2067) in comparison with theamplitude, |z(t; d; )|, of the quadrature demodulated signal (|z(t0 ; d2 ; 1 )|/|z(t0 ; d1 ; 1 )| = 1.0) as shown in Fig. 3.
From this result, fcost (d; ) could be eﬀective for diﬀerentiation of the arterial wall from the lumen.
C. Diﬀerentiation by Spatial Derivative of theCost Function
To increase the diﬀerence between the arterial wall andthe lumen, the spatial derivative, dfcost (d; ), of the cost

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function is used for detection of the lumen-intima boundary.
Fig. 5(b) shows an enlarged view of the cost function,
fcost (d; 1 ), around the posterior wall at the beam position
1 , as shown in Fig. 2. In the lumen, the cost function has
a small peak, which corresponds to the multiple reﬂection
from the anterior wall or the scattering from the tissue
between the anterior wall and the skin surface. Such peaks
must be suppressed in order to reduce diﬃculties in setting
the threshold level, ρf .
To suppress small peaks in the lumen, the spatial derivative, dfcost (d; ), of the cost function is averaged as theslope of the linear line obtained by applying the leastsquares method to the measured cost function, fcost (d; ),as follows:
COV (d; ),V AR(d; )dfcost (d; ) =

(18)

where
COV (d; ) =1
(Md + 1)(N + 1)





Md /2

N/2

(d + mD) ·m=−Md /2 n=−N/2

fcost (d + mD;  + nL) − d¯ · f¯cost ,1
V AR(d; ) =Md + 1f¯cost =

Md /2(d + mD)2 − d¯ 2 ,(20)

m=−Md /2

1
(Md + 1)(N + 1)





N/2

Md /2

m=−Md /2 n=−N/2

fcost (d + mD;  + nL),d¯ =1
Md + 1

(19)



(21)

Fig. 5. (a) Cost function, fcost (d; 1 ), measured at beam position
1 is plotted as a function of depth. (b) Enlarged view of the costfunction, fcost (d; ), around the lumen-intima boundary at position
1 .

Md /2

(d + mD).

(22)

m=−Md /2

In this paper, the spatial derivative, dfcost (d; ), is obtained as an average value within the region of 3 mm
(Md = 40) in the depth direction in consideration of thewidth of the peak in the cost function, fcost (d; ), which
is about 3 mm around the posterior wall as shown in
Fig. 5(a). In addition, as in (7), dfcost (d; ) is averaged
within N + 1 (N = 2) scan lines by considering the lateralcontinuity of the inner surface of the arterial wall. By averaging the spatial derivative, undesirable small peaks in
the lumen, whose width is less than 3 mm, are suppressed,
and it becomes possible to set a suﬃciently low thresholdlevel. As shown in Fig. 3, the amplitude of echo reﬂectedby the lumen-intima interface is not so large in comparison with that reﬂected by the media-adventitia interface.
Therefore, a low threshold level is necessary to detect thelumen-intima boundary. If the threshold level is not suﬃciently low, the media-adventitia boundary cannot be detected.
Figs. 6(a) and (b) show the spatial derivative,
dfcost (d; ), of the cost function shown in Fig. 5(a)and an enlarged view of Fig. 6(a) around the posteriorwall, respectively. Using the averaged spatial derivative,
dfcost (d; ), undesirable small peaks in the lumen are suppressed.
Supposedly, small peaks in the lumen also can be suppressed by applying smoothing of the cost function. In
Fig. 5, the cost function, which is spatially averaged within
the area of the same size in calculation of spatial derivative by (18), also is plotted by crosses. Although the small
peak in the lumen is suppressed, the smoothed cost function in the lumen also has a positive value, as does asthat around the posterior wall. Therefore, the thresholdlevel for the smoothed cost function becomes rather highin comparison with that for the spatial derivative. However, use of the high threshold level might result in detection of the media-adventitia boundary instead of thelumen-intima boundary. However, the spatial derivative,
dfcost (d; ), has a negative value at the lumen as shown in
Fig. 6. Therefore, the media-adventitia boundary is prevented from being detected by setting a positive thresholdlevel, which can be set smaller than that for the smoothed
cost function, for the spatial derivative.

hasegawa et al.: method for detection of lumen-intima boundary of carotid artery

Fig. 6. (a) Spatial derivative, dfcost (d; ), of the cost function atbeam position 1 . (b) Enlarged view of (a).

III. In vivo Experimental Results for the Human
Common Carotid Artery
A. Detection of Lumen-Intima Boundary by Setting
the Threshold Level to the Amplitude of the Echo
In Fig. 7(b), the detected lumen-intima boundaries areshown as white lines, which are obtained by setting thethreshold level to the amplitude, |z(t; d; )|, of the quadrature demodulated signal. In the amplitude-based detection, |z(t; d; )| of the echo is spatially averaged within anarea that is the same size as that used in calculation of thecost function in (16) and is normalized by the maximum
amplitude within the ROI.
In Fig. 7(b), the threshold level, ρa , is determined byminimizing the root mean square (RMS) error, eRMS , ofthe automatically detected lumen-intima boundary fromthe manually assigned boundary shown in Fig. 7(a). The
RMS error, eRMS , is deﬁned by depths, dcal () and dman (),of the automatically detected boundary and the manuallyassigned boundary at the ultrasonic beam position, , asfollows:b
1 |dcal () − dman ()|2 ,Nb

NeRMS =

=1

(23)

101

Fig. 7. (a) Manually determined lumen-intima boundary (50-year-oldmale). (b) Lumen-intima boundary detected by setting the thresholdlevel to the amplitude, |z(t; d; )|, of the quadrature demodulated
signal.

where Nb is the number of ultrasonic beam positions.
In Fig. 8, eRMS of the automatically detected lumenintima boundary is plotted as a function of the threshold level, ρa , and the optimum threshold level is determined to be 0.19. The threshold level, ρa , for the amplitude, |z(t; d; )|, of the quadrature demodulated signal isexpressed as a ratio of the threshold level to the maximum
amplitude within the ROI. In Fig. 7(b), even under the
optimum threshold setting, error of the detected boundary is still large (eRMS = 555 µm). This result indicatesthat there are diﬃculties in setting the optimum threshold level to |z(t; d; )| of the echo because |z(t; d; )| at thelumen and that at the lumen-intima boundary are not sufﬁciently diﬀerent. Thus, it is diﬃcult to detect the lumenintima boundary only from the amplitude of the echo.
B. Boundary Detection Using the Cost Function
In Fig. 9, the detected lumen-intima boundary is shown
as a white line, which is obtained by setting the threshold level, ρf , to the cost function, fcost (d; ). The threshold level for the cost function is expressed as a ratio of
the threshold level to the maximum value of the costfunction within the ROI. In Fig. 9, ρf is determined byminimizing eRMS of the automatically detected lumenintima boundary from the manually assigned boundary
shown in Fig. 7(a). The optimum threshold level, ρf , is102

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Fig. 8. RMS error, eRMS , of detected lumen-intima boundary determined by setting the threshold level to the amplitude, |z(t; d; )|, ofthe quadrature demodulated signal, is plotted as a function of thethreshold level.

Fig. 10. Lumen-intima boundary of the posterior wall for the samedata shown in Fig. 2 detected from the spatial derivative, dfcost (d; ),of the cost function.

function. The threshold level, ρdf , is determined by minimizing eRMS of the automatically detected lumen-intima
boundary from the manually assigned boundary shown in
Fig. 7(a). By minimizing eRMS of the detected lumenintima boundary, the optimum ρdf is determined to be
0.00013, in which the threshold level is expressed as a ratio of the threshold level to the maximum value of thespatial derivative, dfcost (d; ), within the ROI.
D. Determination of the Threshold Level for Automatic
Boundary Detection

Fig. 9. Lumen-intima boundary detected by setting the thresholdlevel to the cost function, fcost (d; ) (same subject as shown in
Fig. 7).

determined to be 0.0007 by minimizing eRMS of the detected lumen-intima boundary. By using fcost (d; ), eRMSof the detected lumen-intima boundary is much improved(eRMS = 123 µm). However, at some beam positions, large
detection errors, which are indicated by white arrows in
Fig. 9, still remain. The threshold level, ρf , must be lower
than the value of fcost (d; ) at the lumen-intima boundary to correctly detect the lumen-intima boundary at thebeam position surrounded by the oval. However, a threshold level of 0.0007 is necessary to prevent the echo in the lumen from being detected. In order to reduce the thresholdlevel, fcost (d; ) in the lumen must be further suppressed.
C. Boundary Detection by Using the Spatial Derivativeof the Cost Function
In Fig. 10, the lumen-intima boundary of the same subject as depicted in Fig. 9, which is detected using the spatial derivative, is shown as a white line. The RMS error,eRMS , of the detected lumen-intima boundary is improved(eRMS = 119 µm) by using the spatial derivative of the cost

To automatically detect the lumen-intima boundary,
the threshold level must be determined beforehand. In thissection, the threshold level is determined from the data
sets obtained at carotid arteries of 21 subjects (male, 51±7
years old).
In Fig. 11, the threshold level, which gives minimum
RMS error of the detected boundary from the manually determined boundary, is plotted for 21 data sets. Figs. 11(a),(b), and (c) show the threshold levels for the amplitude,|z(t; d; )|, the cost function, fcost (d; ), and the spatial
derivative, dfcost (d; ), respectively. The mean values areused as threshold levels for automatic boundary detectionin the following section.
In Fig. 11, RMS error of the detected boundary is improved using fcost (d; ) or dfcost (d; ) in comparison withuse of |z(t; d; )| of the echo. The standard deviation of the
optimum threshold level for dfcost (d; ) shown in Fig. 11(c)is 35.3% to its mean value of 0.00015. This is smaller
than 47.0% (mean: 0.0010) for fcost (d; ). From these results, dfcost (d; ) is seen to have an advantage in ﬁxing thethreshold level.
E. Automatic Boundary Detection with a ConstantThreshold Level
Using the threshold level determined in Section III-D,
RMS errors of automatically detected boundary are evaluated with respect to four other subjects with and with-hasegawa et al.: method for detection of lumen-intima boundary of carotid artery103

tance measurement using standard ultrasonic diagnostic
equipment. Therefore, the proposed method is suﬃciently
precise for detection of the lumen-intima boundary.

IV. Discussion
A. Elapsed Time for Calculating the Cost Function
When the ROI is composed of Nb beam positions andNd sampled points in the direction of depth, the elapsed
time, Ttotal , required for calculation of the spatial derivative, fcost (d; ), of the cost function is estimated as follows:
Ttotal = Tcost + Tspd ,(24)

where Tcost and Tspd are the elapsed time for calculationof the cost function, fcost (d; ), and that for calculation of
the spatial derivative, fcost (d; ), respectively. In order tosearch for the lumen-intima boundary in the area from thecenter to the end of the ROI, (Nd − Md )/2 spatial derivatives, dfcost (d; ), each of which is estimated from Md + 1
cost functions, fcost (d; ), by (18), must be obtained, andfor this purpose, (Nd + Md )/2 cost functions, fcost (d; ),are calculated. Therefore, Tcost and Tspd are estimated asfollows:
Nd + M d
× 21.7 (µs),
2
Nd − M d
Tspd = Nb ×× 24.3 (µs).
2

Tcost = Nb ×

Fig. 11. RMS error, eRMS , is plotted as a function of threshold levelfor 21 subjects. (a) Amplitude, |z(t; d; )|, of echo. (b) Cost function,
fcost (d; ). (c) Spatial derivative, dfcost (d; ), of cost function.

out atherosclerotic plaque. In Fig. 12, the lumen-intima
boundary for each subject, which was determined using
dfcost (d; ), is shown as a white line. Good results wereobtained for these four subjects as shown in Fig. 12, evenwhen there was atherosclerotic plaque on the arterial wall[Fig. 12(b,4)].
The RMS errors, eRMS , of the automatically detected
lumen-intima boundaries of each subject—which are evaluated using the amplitude, |z(t; d; )|, of the quadrature
demodulated signal, cost function, fcost (d; ), and spatial
derivative, dfcost (d; ), of the cost function—are plotted inFig. 13. For each subject, eRMS is large when |z(t; d; )|of the quadrature demodulated signal is used. The RMS
error, eRMS , is reduced to about 0.1 mm using dfcost (d; ).
It almost corresponds to the minimum resolution in dis-

(25)
(26)

Using a typical data set, elapsed times of 21.7 µs and24.3 µs in (25) and (26) are determined by measuring
Tcost and Tspd using a computer with the Intel Pentium
III 1.2 GHz CPU (Intel Corporation, Santa Clara, CA)and dividing measured Tcost and Tspd by Nb (Nd + Md )/2and Nb (Nd − Md )/2 (number of data points), respectively.
As a typical case, the data shown in Fig. 2(b) consist of 60
scan lines and 192 sampled points in the depth direction.
In this case, the total elapsed time, Ttotal , is given by:
192 + 40
× 21.7 × 10−3 + 60
2
192 − 40
×× 24.3 × 10−3 = 262 ms. (27)2

Ttotal = 60 ×

The typical elapsed time of 0.26 s for the calculation isapplicable for real-time measurement of the elasticity of
the arterial wall.
B. Evaluation of Repeatability
To evaluate the repeatability of the proposed method, invivo experiments at the carotid artery were conducted forthree subjects (29-year-old male, 23-year-old male, and 21year-old male). Measurements were performed ﬁve times
for each subject, and the RMS error of the boundary automatically detected from the manually assigned boundary
was evaluated for each measurement. The threshold level,

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Fig. 12. Detected lumen-intima boundaries for four subjects. (a) B-mode image obtained by standard ultrasonic diagnostic equipment.
(b) B-mode image reconstructed from the amplitude, |z(t; d; )|, of the quadrature demodulated signal. (1) 40-year-old male (A) withoutatherosclerotic plaque. (2) 37-year-old male without atherosclerotic plaque. (3) 40-year-old male (B) without atherosclerotic plaque. (4) 57year-old male with atherosclerotic plaque.

hasegawa et al.: method for detection of lumen-intima boundary of carotid artery

Fig. 13. RMS error, eRMS , of the detected lumen-intima boundaries
of each subject determined using the amplitude, |z(t; d; )|, of thequadrature demodulated signal, cost function, fcost (d; ), and spatial
derivative, dfcost (d; ), of the cost function.

105

In the boundary detection of the anterior wall using
dfcost (d; ), the threshold level must be higher than thatin detection of the posterior wall because there are manysignals in the lumen around the anterior wall due to theinﬂuence of the multiple reﬂection from the anterior walland scattering from the tissue between the anterior walland the skin surface. Fig. 15(a) shows the detected lumenintima boundary of the anterior wall for the same data
shown in Fig. 2(b) using the spatial derivative, dfcost (d; ),of the cost function. To improve the detection error, thedetected boundary is laterally averaged within ± ﬁve ultrasonic beam positions. The threshold level is set at 0.0019
with the same procedure as described in Section III-D
using 21 data sets. In Fig. 15(a), the detection error islarge due to the signals in the lumen. Supposedly theluminal boundary of the anterior wall can be approximately detected from the maximum gradient of the peakin dfcost (d; ) in the vicinity of the anterior wall. For this
purpose, the second order spatial derivative, fcost(d; ), of
the cost function is obtained as shown in Fig. 15(c) by applying the same procedure as described in Section II-C todfcost (d; ) as follows:(d; ) =fcost

COV2 (d; ),V AR2 (d; )

(28)

where
COV2 (d; ) =1
(Md2 + 1)(N + 1)

Md2 /2N/2m=−Md2 /2 n=−N/2(d + mD) · dfcost (d + mD;  + nL) (29)− d¯ · df,
costFig. 14. Mean value and standard deviation of RMS error in thedetected lumen-intima boundary of the posterior wall for ﬁve measurements. Mean values and standard deviations are evaluated forthree subjects (29-year-old male, 23-year-old male, and 21-year-oldmale).

V AR2 (d; ) =df cost =which was determined in Section III-D, was used. Fig. 14
shows mean values and standard deviations of RMS error of the detected lumen-intima boundary of the posterior wall for ﬁve measurements with respect to the threesubjects. In Fig. 14, the RMS error of the detected boundary is improved using the proposed cost function in comparison with the amplitude-based detection. Furthermore,
the lumen-intima boundary was detected with good reproducibility for ﬁve measurements using the proposed costfunction.
C. Boundary Detection of the Anterior WallIn this paper, a method for detection of the lumenintima boundary of the posterior wall is proposed. However, to obtain the elastic modulus by (4), the luminalboundary of the anterior wall must be detected to obtain
the inner radius, r0 , of the artery.

1
Md2 + 1

Md2 /2(d + mD)2 − d¯ 2 ,(30)

m=−Md2 /2

1(Md2 + 1)(N + 1)

Md2 /2m=−Md2 /2 n=−N/2

dfcost (d + mD;  + nL),d¯ =1
Md2 + 1





N/2

(31)

Md2 /2(d + mD),(32)

m=−Md2 /2

where Md2 is set at 4.
Fig. 15(b) shows the luminal boundary detected from
the positive peak of fcost(d; ). As well as Fig. 15(b), theluminal boundaries of the anterior wall are detected for
four other data shown in Fig. 12, and the RMS error ofthe detected boundary from the manually assigned boundary for each data set is evaluated as shown in Fig. 15(d).
In Fig. 15(d), the RMS error is improved using fcost(d; ).
However, the RMS error is rather large in comparison withthe case of the posterior wall using dfcost (d; ). To improvethe boundary detection of the anterior wall, further investigation is necessary to develop a method for further
suppression of the signals in the lumen.

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Fig. 15. Boundary detection of the anterior wall. (a) Detected boundary using the spatial derivative, dfcost (d; ), of the cost function.
 (d; ). (c) df
(b) Detected boundary using the second order spatial derivative, fcost
cost (d; 1 ) and fcost (d; 1 ) plotted as a function of depth.
(d) RMS errors, eRMS , of the detected boundaries for ﬁve subjects.

V. Conclusions
In this paper, we have proposed the use of the cost function for diﬀerentiation of the arterial wall from the lumen.
From ﬁndings of in vivo experiments, it was shown thatthe lumen-intima boundary can be detected with an errorof about 0.1 mm using the proposed cost function. This error is somewhat worse than that with other sophisticatedmethods based upon the amplitude of the echo. Using asingle M-line signal, Hoeks et al. [40] detected the lumenintima boundary with an error of 0.044 mm. Although
their method achieves high accuracy using the temporally
averaged envelope of the RF signal, the displacements ateach depth along an ultrasonic beam must be estimatedprior to temporal averaging of the envelope. Therefore, alarge amount of computation is necessary to apply thismethod to the B-mode (many M-lines) images.
Although the accuracy of the proposed method is somewhat worse than that of such a sophisticated method, theproposed method requires only short analysis time (0.26 s,
Pentium III 1.2 GHz) and thus is useful for the real-timemeasurement of the elasticity of the arterial wall. However,a method for detection of the outer boundary of the adventitia of the posterior wall and the luminal boundary of theanterior wall also must be established through further investigation to realize the real-time elasticity measurementby our method.
Acknowledgment
The authors would like to thank Dr. Jens E. Wilhjelm
at the Technical University of Denmark for general discussions. The authors also acknowledge the comments madeby the reviewers.

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Hideyuki Hasegawa was born in Oyama,
Japan, in 1973. He received the B.E. degree inelectrical engineering from Tohoku University,
Sendai, Japan, in 1996. He received the Ph.D.
degree in electrical engineering from Tohoku
University in 2001. He is presently a research
associate of Graduate School of Engineering of
Tohoku University. His main research interestis medical ultrasound, especially diagnosis ofatherosclerosis based on measurement of mechanical properties of arterial wall.
Dr. Hasegawa is a member of the IEEE,
the Acoustical Society of Japan, the Japan Society of Ultrasonics in
Medicine, and the Institute of Electronics, Information and Communication Engineers.

Hiroshi Kanai (A’88–M’91) was born in
Matsumoto, Japan, on November 29, 1958. Hereceived the B.E. degree in electrical engineering from Tohoku University, Sendai, Japan in
1981, and the M.E. and Ph.D. degrees, also
from Tohoku University, in 1983 and in 1986,
both in electrical engineering.
From 1986 to 1988 Dr. Kanai was with the
Education Center for Information Processing,Tohoku University, as a research associate.
From 1990 to 1992 he was a lecturer in the Department of Electrical Engineering, Faculty ofEngineering, Tohoku University. From 1992 to 2001 he was an associate professor in the Department of Electrical Engineering, Facultyof Engineering, Tohoku University. Since 2001 he has been a professor in the Department of Electronic Engineering, Graduate Schoolof Engineering, Tohoku University.
His present interests are in ultrasonic measurement and digital
signal processing for diagnosis of heart diseases and arteriosclerosis.
Dr. Kanai is a member of the IEEE, the Acoustical Society ofJapan, the Institute of Electronics Information and Communication
Engineering of Japan, the Japan Society of Mechanical Engineers, the108ieee transactions on ultrasonics, ferroelectrics, and frequency control, vol. 51, no. 1, january 2004

Japan Society of Ultrasonics in Medicine, Japan Society of Medical
Electronics and Biological Engineering, and the Japanese Circulation
Society.

Yoshiro Koiwa was born in Sendai, Japan,
in 1944. He graduated from Tohoku University, Sendai, Japan, in 1969. He received theM.D. degree from Tohoku University in 1977.
He is presently an associate professor ofinternal medicine of Tohoku University. His
main research interest is cardiovascular disease, especially cardiac function and heart
failure.
Dr. Koiwa is a member of the Japanese
Circulation Society, and the Japan Society of
Medical Electronics and Biological Engineering.