Author Type

Graduate Student

Date of Award

2017

Document Type

Thesis

Publication Status

Version of Record

Submission Date

October 2026

Thesis/Dissertation Advisor [Chair]

Aalo, Valentine A.

Abstract

Modern cancerous tumor diagnostics is nearly impossible without invasive methods, such as biopsy, that may require involved surgical procedures. In recent years some work has been done to develop alternative non-invasive methods of medical diagnostics. For this purpose, the data obtained from an ultrasound image of the body crosssection, has been analyzed using statistical models, including Rayleigh, Rice, Nakagami, and K statistical distributions. The homodyned-K (H-K) distribution has been found to be a good statistical tool to analyze the envelope and/or the intensity of backscattered signal in ultrasound tissue characterization. However, its use has usually been limited due to the fact that its probability density function (PDF) is not available in closed-form. In this work we present a novel closed-form representation for the H-K distribution. In addition, we propose using the first order approximation of the H-K distribution, the I-K distribution that has a closed-form, for the ultrasound tissue characterization applications. More specifically, we show that some tissue conditions that cause the backscattered signal to have low effective density values, can be successfully modeled by the I-K PDF. We introduce the concept of using H-K PDF-based and I-K PDF-based entropies as additional tools for characterization of ultrasonic breast tissue images. The entropy may be used as a goodness of fit measure that allows to select a better-fitting statistical model for a specific data set. In addition, the values of the entropies as well as the values of the statistical distribution parameters, allow for more accurate classification of tumors.

Extent

130 p.

Comments

Includes bibliography.|Thesis (M.S.)--Florida Atlantic University, 2017.|FAU Electronic Theses and Dissertations Collection|Includes bibliography.

Identifier

FA00004922

Format

pdf

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