Access Type

Open Access Dissertation

Date of Award

January 2010

Degree Type

Dissertation

Degree Name

Ph.D.

Department

Physics and Astronomy

First Advisor

Zhi-Feng Huang

Second Advisor

Nebojsa Duric

Abstract

Conventional ultrasound techniques use beam-formed, constant sound speed ray models for fast image reconstruction. However, these techniques are inadequate for the emerging new field of ultrasound tomography (UST). We present a new technique for reconstruction of reflection images from UST data. We have extended the planar Kirchhoff migration method used in geophysics, and combined it with sound speed and attenuation data obtained from the transmission signals to create reflection ultrasound images that are corrected for refractive and attenuative effects.

The resulting techniques were applied to simulated numerical phantom data, physical phantom data and in-vivo breast data obtained with an experimental ring transducer prototype. Additionally, the ring transducer was customized to test compatibility with an existing ultrasound workstation. We were able to obtain independently recorded radio-frequency (RF) data for individual transmit-receive pair combinations for all 128 transducers. The signal data was then successfully reconstructed into reflection data using the Kirchhoff migration techniques.

The results from the use of sound speed and attenuation corrections lead to significant improvements in image quality, particularly in dense tissues where the refractive and scattering effects are the greatest. The procedure was applied to a variety of breast densities and masses of different natures. The resulting reflection images successfully resolved boundaries and textures.

The reflection characteristics of tomographic ultrasound maintain an indispensible position in the quantification of proper mass identification. The results of this project indicate the clinical significance of the invocation of properly compensated Kirchhoff based reconstruction method with the use of sound speed and attenuation parameters for the visualization and classification of masses and tissue.

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