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Browsing by Author "Santago, Peter"

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    How to Define the Next Generation Cardiac CT Architecture? - a Contemporary Challenge for Interdisciplinary Collaboration
    Yu, Hengyong; DeMan, Bruno; Carr, Jeff; Frontera, Mark; Zeng, Kai; Bennett, James; Fitzgerald, Paul; Iatrou, Maria; Shen, Haiou; Santago, Peter; Wang, Ge (2010-05-21)
    Cardiovascular diseases are pervasive with high mortality and morbidity at tremendous social and healthcare costs. There are urgent needs for significantly higher fidelity cardiac CT with substantially lower radiation dose, which is currently not possible because of technical limitations. Although cardiac CT technology has improved significantly from 16 to 320 detector rows and from single to dual source, there remain technical challenges in terms of temporal resolution, spatial resolution, radiation dose, and so on. Based on an ideal academic-industrial partnership between Virginia Tech and the GE Global Research Center (GEGR), we are motivated to advance the state-of-the-art in cardiac CT. The overall goal of this project is to develop novel cardiac CT architectures and the associated reconstruction algorithms, and define the next-generation cardiac CT system. The specific aims are to (1) design, analyze and compare novel cardiac CT architectures with novel sources and scanning trajectories; (2) develop analytic and iterative cardiac CT reconstruction algorithms for ROI-oriented scanning and dynamic imaging for the proposed cardiac CT architectures; and (3) evaluate and validate the proposed architectures and algorithms in theoretical studies, numerical simulations, phantom experiments and observer studies. On completion of this project, we will have singled out the most promising cardiac CT architectures and algorithms to achieve 16cm coverage, 50ms temporal resolution, 20lp/cm spatial resolution, 10HU noise level, and 1mSv effective dose simultaneously for the entire examination, with detailed specifications and performance evaluation, setting the stage for prototyping a next-generation cardiac CT system in a Phase-II project. This project will enable significantly better diagnostic performance and bring major therapeutic benefits that affect over 60 million Americans.
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    Reconstruction Methods for Optical Molecular Tomography
    Cong, Alexander Xiao (Virginia Tech, 2013-01-25)
    Molecular imaging plays an important role for development of systems biomedicine, which non-invasively extracts pictorial information on physiological and pathological activities at the cellular and molecular levels. Optical molecular tomography is an emerging area of molecular imaging. It locates and quantifies a 3D molecular probe distribution in vivo from data measured on the external surface of a small animal around the visible and infrared range. This approach can facilitate or enable preclinical applications such as cancer studies, involving angiogenesis, tumor growth, cell motility, metastasis, and interaction with a micro-environment. The reconstruction of diffuse light sources is the central task of optical molecular tomography, and generally ill-posed and rather complex. The key element of optical molecular tomography includes the geometrical model, tissue properties, photon characteristics, transport model, and reconstruction algorithm. This dissertation focuses mainly on the development optical molecular tomography methods based on bioluminescence/fluorescence probes to solve some well-known challenges in this field. Our main results are as follows. We developed a new algorithm for estimation of optical parameters based on the phase-approximation model.  Our iterative algorithm takes advantage of both the global search ability of the differential evolution algorithm and the efficiency of the conjugate gradient method. We published the first paper on multispectral bioluminescence tomography (BLT). The multispectral BLT approach improves the accuracy and stability of the BLT reconstruction even if data are highly noisy. We established a well-posed inverse source model for optical molecular tomography. Based on this model, we proposed a differential evolution-based reconstruction algorithm to determine the source locations and strengths accurately and reliably. Furthermore, to enhance the spatial resolution of fluorescence molecular tomography, we proposed fluorescence micro-tomography to image cells in a tissue scaffold based on Monte Carlo simulation on a massive parallel processing architecture. Each of these methods shows better performance in numerical simulation, phantom experiments, and mouse studies than the conventional methods.