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EFFICIENT IMPLEMENTATION OF CLUTTER EIGENFILTERS

In this chapter, one of th e classical challenges involved in C FI will be discussed, namely clutter rejection. F irst of all, a brief introduction abo ut c lu tter and clu tter rejection is given, followed by the literature review of existing clu tter filters. T hen, an efficient im plem entation of the recently developed eigenfilters using a fast subspace tracking technique is introduced, w ithout degrading the perform ance as com pared to employing conventional block EV D /SVD based eigenfilters.

5.1 C lutter Rejection

In ultrasound Doppler blood flow m easurem ents, the backscattered signals from the moving blood scatterers are corrupted by interference signals, term ed clutter, originating from the stationary or slowly-moving tissue such as vessel walls, and from statio n ary reverberations. [Jen96a,EM 00,EFPF97, SchOl]. T he m easured ultrasonic signal resulting from the n th pulse at depth k, denoted r(/c,n ), can th us be well modelled as consisting of three statistically independent com ponents [BTK02], i.e.,

x( k, n ) = c(k, n) + b(k, n) + w(k, n), (5.1.1)

S e c t i o n 5 .1 . C lu t t e r R e j e c t io n 8 0

Filter frequency response Clutter

Blood

Filter frequency response Clutter

Blood

Frequency shift

(a) (b)

F ig u r e 5 .1 . T h e frequency s p e c tra of c lu tte r, b lood an d noise co n tain ed in dem o du lated com plex R F d a ta , assum ing th e D o ppler shift is positiv e for m otio n tow ards probe. T he d o tted line rep resen ts an ideal high -pass filter, (a) w ith s ta tio n a ry tissue; (b) w ith slow- moving tissue.

where c(k, n ), b( k, n ) an d w(k, n) d e n o te th e c lu tte r, th e blood an d th e ad d itiv e noise com po­ nents, respectively. Typically, th e c lu tte r signals are 20 - 60 dB stro n g er th a n th e backscat- tered signals from th e b lood s c a tte rs [H vdV D ^O l, Jen93b, EM00]. O n th e o th e r hand, the echoes scattered from rap id ly m oving blood cells have larger frequency shifts th a n th e echoes scattered from slowly m oving tissu e. F ig ure 5.1 d ep icts th e frequency sp e c tra of th e three com ponents w ith or w ith o u t m oving tissue. For c lu tte r w hich orig in ates from th e sta tio n a ry tissue, shown in F igure 5.1 (a), th e c lu tte r co m p o n en t will rem ain identical in each R F line w ithin each LOS. As a resu lt, th e s ta tio n a ry c lu tte r signals can be filtered out by using a

S e c tio n 5 .1 . C lu tte r R e je c tio n 81

simple difference filter (also called stationary echo cancelling) [Jen93b], i.e.,

yk(n) = a Tx fc(n) (5.1.2)

where a = ■1

T

. However, the clutter com- and Xjt(n) = x ( k , n ) x ( k , n — 1)

ponent will not be strictly identical in each R F line due to tissue m otion induced by the pulsating vessels. This leads to sp ectra overlap between blood and clu tter in a common fre­ quency band as shown in F igure 5.1 (b). T his situation occurs quite commonly in blood flow measurement, especially in strain-flow imaging which is a new technique for investigating the vascular dynamics and tum o r biology [KHTI03]. As in tum or imaging, th e blood and clutter echoes often share the sam e frequency bands under low flow velocity conditions, making the separation of blood and clu tte r very challenging. T he adverse influence of clutter can be reduced by minimizing th e size of the echo sample volume, b u t even if th e entire sample volume is inside a blood vessel, th e unavoidable clu tter from reverberations and transducer side lobes will affect the signal [KHTI03]. Furtherm ore, blood velocities are commonly esti­ m ated by using th e au tocorrelation m ethod [KNK085]. To o btain unbiased blood velocity estimates, the clu tter signals need to be atten u ated down to th e th erm al noise level and an efficient clutter filter m ust be applied before th e estim ation. Since clu tter filters operate along the slow tim e axis, only 4 — 20 echo samples are available for high pass filtering to m aintain acceptable fram e ra te [EM00].

Thus, an ideal clu tter filter should exhibit th e following properties: • Narrow tran sition band;

• Being adaptive to no n -statio n ary clutter;

• Not reducing th e lim ited available d a ta samples; • Not removing blood com ponent.

S e c tio n 5 .1 . C lu tter R e je c tio n 82

Clutter

filters

Static filters

FIR HR R Static poly. reg. ) e

---ICA

Down-mixing

ERF/PCA ) 0

n