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University of Balamand > Academics > Research > Seminars > Jihad Daba

Speckle Noise: An Advancement from 'Worthless Nuisance' to 'Carrier of Information' for Features Extraction in Radar and Ultrasound Images

Tuesday, April 03, 2007 from 12:30 to 13:30 at Jacobo Auditorium

SUBMITTED BY: Dr. Jihad Daba
Faculty of Engineering
University of Balamand

ABSTRACT: Detection, estimation, and classification in images formed by coherent imaging systems such as radars and ultrasound systems are complicated by the presence of speckle noise. Speckle not only complicates these problems for human specialists, but also for machine detection and identification algorithms. In this work, we choose B-scan ultrasound systems as an application target. We treat speckle form a novel point of view: as a carrier of useful clinical information about tissue characteristics rather than as contaminating noise. The stochastic models for tissue scattering are based on a doubly stochastic compound marked Poisson point process. For each of these tissue scattering statistical models, we present estimation algorithms to determine the average tissue local scatterer density or concentration of scattering elements using intensity measurements of speckled images (echoes). We show that the maximum likelihood (ML) estimator is optimal in the sense that the variance of the error is the smallest possible using any other conceivable estimate having the same bias with the same data. In addition to their important applications in quantitative biological tissue classification and characterization (an area of paramount importance for computer-assisted tissue classification and medical diagnosis), these estimation algorithms can also serve as a powerful tool for estimating radioactive concentration in nuclear medicine (NM) imaging and for image reconstruction in tomography.
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