|University of Illinois at Urbana-Champaign | Department of Electrical and Computer Engineering | Department of Bioengineering
Department of Statistics | Coordinated Science Laboratory | Beckman Institute | Food Science and Human Nutrition | Division of Nutritional Sciences | College of Engineering
|Sunday, November 19th, 2017|
Coded Excitation and Pulse CompressionBy José Sánchez, Graduate Student
Darren Pocci, Student
Professor Michael L. Oelze
A coded excitation and pulse compression technique was recently developed, resolution enhancement compression (REC), which allow the axial resolution and bandwidth of the imaging system to be enhanced . In addition to improvements in terms of axial resolution, the REC technique has the typical coded excitation and pulse compression benefits, such as deeper penetration due to improvement in echo signal-to-noise ratio (eSNR).
The main advantage of the REC technique is capability to shape and select to a limited degree certain desired characteristics of an ultrasonic imaging system through coded excitation and pulse compression. A preenhanced chirp, which is found using convolution equivalence in the frequency domain, is used to selectively excite an ultrasonic source with different energies at chosen frequencies. Figure 1 shows convolution equivalence in time domain.
After exciting the source with a preenhanced chirp (Fig 1b), the received signal is compressed using a Wiener filter based on convolution equivalence. The envelope of the REC waveform (impulse response with double bandwidth) reflected from a point scatterer in an attenuated media (0.5 dB/cm/MHz) and the envelope for conventional pulsing (CP) methods are shown in Fig. 2a. The PSD of REC waveform and CP methods are shown in Fig. 2b to illustrate the bandwidth enhancement that was achieved by using the REC technique.
The main benefit of using REC is that the characteristics of the impulse response of the imaging system could be tailored to have useful properties for particular imaging applications. These are the applications that currently are being investigated.
I. Lesion contrast enhancement
Frequency compounding (FC) divides the spectrum of the radio-frequency echoes into subbands to make separate images. These separate images can then be added together to reduce the speckle by reducing the image intensity variance. The main disadvantage introduced by using frequency compounding is the inherent tradeoff between axial and contrast resolution. Therefore, the goal of this study was to combine the REC technique with frequency compounding (FC), which will be described as REC-FC, to extend the tradeoff of loss in axial resolution versus enhancement in contrast.
Four subband FC cases were evaluated: full-, half-, third-, and fourth-width of the true impulse response bandwidth. Various image quality metrics were used to assess the improvements obtained by using REC-FC when compared to conventional pulsing (CP) and CP-FC. The image quality metrics used were: contrast-to-noise ratio (CNR), speckle signal-to-noise ratio, histogram pixel intensity, and lesion signal-to-noise ratio. The improvements in terms of CNR, sSNRB, sSNRT and lSNR are shown in Fig. 4. The simulated B-mode images representing these results are displayed in Fig. 5. Histograms of the background and target regions of simulated results for all four cases are shown in Fig. 6.
II. Spectral Imaging
Quantitative ultrasound imaging techniques are currently being evaluated in conjunction with the REC technique. Variance in spectral property estimates is inversely proportional to the bandwidth of the imaging system . Therefore, the objective of this study is to increase the useable bandwidth of the imaging system using REC in order to reduce the variance of scatterer size estimates from the backscattered power spectrum. In addition, reduction in the variance of scatterer size estimates are obtained at deeper depths because of the increase in eSNR by using coded excitation and pulse compression. Reducing the variance of these property estimates may allow the ability to distinguish between healthy and diseased (cancerous) tissues.
|Bioacoustics Research Lab.|