From a fundamental perspective, image reconstruction tasks in both ultrasound pulse echo and photoacoustic imaging are identical. We propose a C-scan imaging scheme that is applicable to both modalities where the image reconstruction is achieved through focusing action of an acoustic lens. The theory to characterize the imaging system is presented. Experimental methodology to determine the system point-spread-function is outlined and demonstrated with preliminary results.

Analysis of ultrasound speckle texture will provide us information about the underlying properties of tissue, could find applications in early lesion detection and tissue characterization. Traditional first and second order statistics based approaches ignore the higher order statistics information in the texture. On the other hand, conventional multichannel filtering or multiresolution analysis approaches rely on the predefined analytical bases which are not fully adaptive to the data being analyzed. In this paper Independent Component Analysis (ICA), which is based on higher order statistics, is proposed to deal with the ultrasound speckle texture analysis problem. ICA image bases obtained from the training images are applied as a filter bank to the testing images. Then the independent features containing higher order statistics information can be extracted from the marginal distributions of the filtered images. ICA is used here as a dimensionality reduction tool to overcome the difficulty of estimating high dimensional joint density of texture. Support Vector Machine (SVM) is then used as a classifier to classify the tissues. By using the digitally simulated tissues and corresponding B-scan images, we can further correlate the change of tissue microstructure or change of imaging conditions with the change of the ICA feature vectors. Our numerical simulation has shown ICA to be a promising technique for ultrasound speckle texture analysis and tissue characterization compared with some traditional methods such as PCA and Gabor transform.

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We developed a novel acoustic plate mode (APM) sensor' for

In medical ultrasonic imaging the signal reflected from the tissue often has a random character to it. It is believed that the random nature of the tissue scattering microstructure is responsible for the stochastic nature of the echo signal. Chen, et. a!. have proposed a signal processing scheme that is based on the statistical moments calculated on the Fourier transform of the time gated echo signal. The theory requires the knowledge of a frequency-dependent effective cell volume term. This paper describes the use of a closed form expression (Lommel diffraction formulation) for this purpose. Our simulation results suggest that reliable estimation of the cell volume is possible only when the time duration of the excitation pulse is small compared to the time gate length.