Nghia Q. Nguyen

Learn More
A first-principles task-based approach to the design of medical ultrasonic imaging systems for breast lesion discrimination is described. This study explores a new approximation to the ideal Bayesian observer strategy that allows for object heterogeneity. The new method, called iterative Wiener filtering, is implemented using echo data simulations and a(More)
This paper describes a task-based, information-theoretic approach to the assessment of image quality in diagnostic sonography. We expand the Kullback-Leibler divergence metric J, which quantifies the diagnostic information contained within recorded radio-frequency echo signals, into a spatial-frequency integral comprised of two spectral components: one(More)
Beamforming of received pulse-echo data generally involves the compression of signals from multiple channels within an aperture. This compression is irreversible, and therefore allows the possibility that information relevant for performing a diagnostic task is irretrievably lost. The purpose of this study was to evaluate information transfer in beamforming(More)
In this paper, we explore relationships between the performance of the ideal observer and information-based measures of class separability in the context of sonographic breast-lesion diagnosis. This investigation was motivated by a finding that, since the test statistic of the ideal observer in sonography is a quadratic function of the echo data, it is not(More)
— We have been developing the ideal observer formalism for sonography, which is based on the best-possible diagnostic performance. The ideal performance was compared to that of trained human observers to estimate the visual efficiency for discriminating lesion features. We find that humans are generally less than 10% efficient at accessing visual(More)
— We show that the minimum-variance (MV), Wiener-filtered (WF), and other beamformers can be derived as approximations to the ideal-observer's strategy for lesion feature discrimination. We analyze breast lesion discrimination performance for five beamformers. Four of the five include matching filtering of receive-channel signal before summation, because(More)
Recently, neural networks have demonstrated their ability to achieve excellent performance for the control of mobile robots. In fact, the recourse of this control method by learning has become a necessity because control systems obtain then, proceed by collecting empirical data, storing and removing the knowledge contained in it and using this knowledge to(More)
Virtually every area of ultrasonic imaging research requires accurate estimation of the spatiotemporal impulse response of the instrument, and yet accurate measurements are difficult to achieve. The impulse response can also be difficult to predict numerically for a specific device because small unknown perturbations in array properties can generate(More)
Finding alternative paths to follow is essential to travelers in dense city bus networks. A simple method is to transform the city bus networks into directed graph and then apply a standard K-shortest-path algorithm to the graph to find alternative paths. However, as the constructed graph is often massive and complex, classical K-shortest-path algorithms(More)