Programmable imaging with two-axis micromirrors.

We demonstrate a means of creating a digital image by using a two-axis tilt micromirror to scan a scene. For each different orientation we extract a single gray scale value from the mirror and combine them to form a single composite image. This allows one to choose the distribution of the samples, and so in principle a variable resolution image could be created. We demonstrate this ability to control resolution and projection by constructing a voltage table that compensates for the nonlinear response of the mirrors to the applied voltage.

Benign versus malignant classification of breast tumors based on the the PLSN model for the ultrasound RF echo and homomorphic filtering.

The Power-law Shot Noise (PLSN) model has been recently proposed for modeling the ultrasound radio-frequency echo. According to it, the spectrum of the in-phase/quadrature/envelope components are power-law functions. The corresponding power-law exponents were shown to possess good tissue characterization ability. A crucial step in the computation of in-phase/quadrature/envelope components is the estimation of the echo center frequency at different depths. We here propose a robust way of estimating the center frequency. We employ a well known convolutive model for the rf echo that views the echo as convolution of the tissue response and a component that represents the combined effect of the ultrasound impulse response and frequency dependent attenuation. Via low-pass filtering in the cepstrum domain, the combined ultrasonic contribution and attenuation term is extracted and used to estimate the center frequency. Furthermore, the tissue contribution is used to construct two new tissue characterization features. ROC analysis of 65 clinical ultrasound images of the breast indicates that the proposed features combined yield an area of 0.963.