Browsing by Author "Wyatt, Christopher Lee"
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- Missing data estimation in fMRI dynamic causal modelingZaghlool, Shaza B.; Wyatt, Christopher Lee (Frontiers, 2014-07-04)Dynamic Causal Modeling (DCM) can be used to quantify cognitive function in individuals as effective connectivity. However, ambiguity among subjects in the number and location of discernible active regions prevents all candidate models from being compared in all subjects, precluding the use of DCM as an individual cognitive phenotyping tool. This paper proposes a solution to this problem by treating missing regions in the first-level analysis as missing data, and performing estimation of the time course associated with any missing region using one of four candidate methods: zero-filling, average-filling, noise-filling using a fixed stochastic process, or one estimated using expectation-maximization. The effect of this estimation scheme was analyzed by treating it as a preprocessing step to DCM and observing the resulting effects on model evidence. Simulation studies show that estimation using expectation-maximization yields the highest classification accuracy using a simple loss function and highest model evidence, relative to other methods. This result held for various dataset sizes and varying numbers of model choice. In real data, application to Go/No-Go and Simon tasks allowed computation of signals from the missing nodes and the consequent computation of model evidence in all subjects compared to 62 and 48 percent respectively if no preprocessing was performed. These results demonstrate the face validity of the preprocessing scheme and open the possibility of using single-subject DCM as an individual cognitive phenotyping tool.
- SBES Advanced Multi-scale CT Facility at Virginia Tech - From Multi-scale to Multi-energy and Multi-Parameter Imaging CapabilitiesWang, Ge; Wyatt, Christopher Lee; Yu, Hengyong; Sharma, Kriti S.; Prater, Mary R.; Xiao, Shuhai; Markert, Chad; Saul, Justin; Fox, Edward A.; Lee, Seung W.; Feser, Michael; Lau, S. H.; Yun, Wenbing; Wang, Steve (2010-04-05)While clinical CT scanners are available at our medical school, for preclinical imaging we have a Scanco micro-CT scanner, an Xradia micro-CT scanner and an Xradia nano-CT scanner. With all these scanners, we can cover image resolution and sample size over six orders of magnitude. The Scanco scanner has resolution 16 µm and FOV 20-38 mm. The Xradia micro-CT scanner, purchased using an NIH SIG grant in 2008, is the highest resolution micro-CT system on the market. It produces 0.5 µm resolution and handle samples of up to 100 mm diameter. The Xradia nano-CT scanner, purchased using an NSF-MRI grant in 2009, has 50 nm resolution and represents the state-of-the-art. It allows tomographic imaging in either the attenuation or Zernike phase contrast mode. For the high-resolution performance of the micro-/nano-CT systems, special housing is vital to ensuring technical development and biomedical applications. We have a dedicated space for these systems in the Institute for Critical Technologies and Applied Sciences (ICTAS; http://www.ictas.vt.edu) Building A, adjacent to the Nanoscale Characterization and Fabrication Lab (NCFL; http://www.ictas.vt.edu/NCFL) at Virginia Tech, which hosts most other cutting-edge imaging systems under one roof.
- X-Ray Phase-Contrast Imaging with Three 2D GratingsJiang, Ming; Wyatt, Christopher Lee; Wang, Ge (Hindawi, 2008-03-24)X-ray imaging is of paramount importance for clinical and preclinical imaging but it is fundamentally restricted by the attenuation-based contrast mechanism, which has remained essentially the same since Roentgen's discovery a century ago. Recently, based on the Talbot effect, groundbreaking work was reported using 1D gratings for X-ray phase-contrast imaging with a hospital-grade X-ray tube instead of a synchrotron or microfocused source. In this paper, we report an extension using 2D gratings that reduces the imaging time and increases the accuracy and robustness of phase retrieval compared to current grating-based phase-contrast techniques. Feasibility is demonstrated via numerical simulation.