Browsing by Subject "Tomography"

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Advanced Array Imaging for Breast and Prostate Sonography
(2010-05-14) Vaidyanathan, Ravi Shankar; Lewis, Matthew Allen
[Abstract from Thesis “Introduction.”] In conventional medical ultrasound such as B-mode imaging, the amplitude of the backscattered ultrasound pulse is used to image tissues along a fixed beam direction [1]. This imaging technique works best in static organs, and it is difficult to image moving organs like the heart. The M-mode imaging technique is better for cardiac applications. For better image resolution, ultrasound tomography systems were developed in which ultrasound data were acquired by transducers placed in a circle around the object [2]. This task of deriving the structure of the object from scattered radiation is known as the inverse scattering problem. The inverse scattering problem is known by several names like reflectivity tomography [3] and diffraction tomography [5, 6, 7] etc. Scattering refers to the effects on wave propagation due to an inhomogeneous medium. Since the inhomogenieties are unknown, the goal is to determine their properties – the spatial variation in density, compressibility, geometrical distribution etc. With the scattered wave field, determining the scatterer is called the inverse problem. As for the geometry of the scattering theory, the scatterer is assumed to be present in a homogeneous reference medium with known properties. Following the notations used in Lehman8, the acoustic pressure, p, in this medium satisfies the Helmholtz equation (2 + k2) p(r) = 0 where the pressure field is given by p(r,t)=p0+p1(r,t) The ambient pressure, p0 is constant. Since the scatterer is present in the reference homogeneous medium, the pressure field can be written as p0(r) = pinc(r) + psc(r) where pinc refers to the incident field and psc is the scattered field. In an ideal situation the incident pressure field is taken as a plane wave pinc(r) = p0 eikz where k is the complex wave number which is given by k=(/c) (1- iM) where M is the compressional viscosity. Now, we are in a position to introduce the integral representations of the scattered field. In the region exterior to the scatterer, the pressure field is given by (2 + k2) p0(r) = 0 Introducing the Green’s function G(r – r’) = eik|r-r’|/|r-r’| that will satisfy the inhomogeneous impulse equation (2 + k2) G(r – r’) = -4(r-r’) Using one of the most frequently used approximations, the Rayleigh-Born approximation we can modify equation (7). At large distance the Green‟s function can be approximated by G(r – r’) ~ eikr/r e-ikr.r’ which holds true for k0r‟2/r <<1. A Fourier diffraction theorem based reconstruction technique using the Born approximation is derived in Radial Reflection Diffraction Tomography (RRDT) [8]. Though my work is concerned with time-domain reconstruction techniques, I will discuss some existing frequency domain reconstruction techniques.
Development of Applications and Quantitative Frameworks for Multispectral Optoacoustic Tomography
(2020-12-01T06:00:00.000Z) O'Kelly, Devin Sean; Danuser, Gaudenz; Bouchard, Richard R.; Lewis, Matthew Allen; Fiolka, Reto; Mason, Ralph P.
The tumor microenvironment is a highly complex system, with variations through space and time that are determined by the interplay of normal and cancerous cells, physiological phenomena, and treatments that can dramatically change the structural or biological dynamics underlying the emergent behaviors. Quantitatively and reliably imaging the microenvironment represents an opportunity to develop diagnostic and prognostic assessment of cancer patients, enabling a fuller understanding of the tumor's evolution, and response to treatments. Multispectral optoacoustic tomography (MSOT), a novel imaging modality, has the potential to reveal the spatiotemporal dynamics of oxygenation at high resolution through the use of multiplexed laser light and has shown promise in advancing both clinical and pre-clinical research. Nevertheless, current methods of analysis often fail to yield sensible data, and are prone to artifacts and quantitative errors that preclude the effective use of this imaging method for diagnostic or prognostic imaging and that add difficulties in downstream analyses. In this work, I developed a battery of methods and tools that bridge the gap of MSOT's theoretical capabilities and the practical realities of its usage. These include a transparent and open-source toolbox for image reconstruction and analysis along with its deployment to a cloud-based workflow service managed by the University of Texas Southwestern Medical Center at Dallas' BioHPC; a simple and scalable method to address spectral aliasing and improve the time resolution and signal-to-noise ratio of dynamic MSOT data; a method to extract quantitative breathing parameters from tomographic imaging data; and a model scheme of the systemic physiology that determines the response to gas-breathing challenges. These developments have laid the groundwork for more rigorous investigations using MSOT for preclinical imaging research.
[Southwestern News]
(2002-05-08) Baxter, Mindy
[UT Southwestern Medical Center News]
(2008-05-26) Morales, Katherine
[UT Southwestern Medical Center News]
(2010-06-03) Rian, Russell