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Program Information

Correction of Dark Current and Image Lag in Multi-Source Carbon Nanotube Imaging Systems

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C Frederick

C Frederick*, D Lalush, S Chang, University of North Carolina, Chapel Hill, NC

SU-E-I-79 Sunday 3:00:00 PM - 6:00:00 PM Room: Exhibit Hall

Purpose:
To correct for dark current and detector image lag in multi-source carbon nanotube (CNT) based imaging systems.

Methods:
CNTs can be used as a novel electron source for X-ray generation. Here a small (~2 kV) gate voltage induces a large electric field at the CNT tip that causes field emission as opposed to thermionic emission. This enables faster switching times and allows miniaturization which aids in the development of stationary multi-source systems. These systems may encounter two key problems: dark current in non-active sources and detector lag. In damaged and perhaps end-of-life devices, sources may develop significant electron output without gate voltage, interfering with images from non-active sources. Although the output is small, it is constant, and continuous integration of detectors compared with small X-ray exposure time magnifies its contribution to the signal. A method based on binary multiplexing is developed to mitigate the dark current contributions possibly extending device lifetime. Having discrete sources, these multi-source systems have coarser angular sampling than rotating systems. This coarser sampling means that the detector signal changes more in adjacent projections than rotating systems exacerbating the effect of detector lag. Since flat panel detectors have a capacitive behavior, readout only removes some charge from pixels. As a result, a device dependent amount (6.6% in our device) of the signal from the current image contributes to the subsequent image. A fast, stable inverse filter separating detector lag has been developed.

Results:
Projection data were simulated based on parameters measured from a multi-source CNT system. Incorporating dark current and image lag phenomena into reconstruction improves contrast to noise ratio.

Conclusions:
These correction methods can be easily implemented on clinical multi-source systems to improve image quality and extend the device's usable lifetime.

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