Contrast imaging is a compelling enhancement for the portable, flat panel-based brain CT scanner currently under
development at Xoran. Due to the relative low temporal resolution of flat panel detectors, enabling tomographic imaging
on such platform requires optimizing the imaging and injection protocols. A dynamic CT head phantom was designed to
facilitate this task. The Dynamic Perfusion and Angiography Model (PAM), mimics tissue attenuation in CT images,
provides physiological timing for angiography and perfusion studies, and moves fluid with properties similar to those of
blood. The design consists of an arterial system, which contains bifurcating vessels that feed into perfusion chambers,
mimicking blood flow through capillaries and smaller vessels, and a venous system, which is symmetrical to the arterial
side and drains the perfusion chambers. The variation of geometry and flow rate in the phantom provides the
physiological total time that fluid spends in the head, and the difference in material densities correlates to CT numbers
for biological tissues. This paper discusses the design of Dynamic PAM and shows experimental results demonstrating
its ability to realistically simulate blood flow. Results of dynamic imaging studies of the phantom are also presented.
Multi-frame blind deconvolution (MFBD) has been shown to be useful for overcoming the blurring effects of turbulence- and instrument-induced aberrations in ground-based imaging of satellites. In this scenario, the object has a finite extent that is often entirely contained within the sensor field-of-view. We report on the generalization of MFBD to accommodate objects that extend beyond the field of view, as would be encountered, for example, in solar and planetary astronomy or in down-looking scenarios. We simulate both down-looking and up-looking scenarios, and vary parameters such as the level of scene illumination and the number of data realizations included. In the simulations, MFBD performance is evaluated by comparing results to the true scenes as well as to reconstructions using more established Phase-Diverse Speckle techniques. Using real data, MFBD reconstructions of solar-granulation scenes are validated by comparison with well-accepted PDS results.
We present preliminary results from a comparison of image estimation and recovery algorithms developed for use with advanced telescope instrumentation and adaptive optics systems. Our study will quantitatively compare the potential of these techniques to boost the resolution of imagery obtained with undersampled or low-bandwidth adaptive optics; example applications are optical observations with IR- optimized AO, AO observations in server turbulence, and AO observations with dim guidestars. We will compare the algorithms in terms of morphological and relative radiometric accuracy as well as computational efficiency. Here, we present qualitative comments on image results for two levels each of seeing, object brightness, and AO compensation/wavefront sensing.
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