A square root analog to digital converter to optimally convert photonic signals for computed tomography
Author(s)
Bieniosek, Matthew (Matthew F.)
DownloadFull printable version (4.772Mb)
Alternative title
Square root ADC converter to optimally convert photonic signals for CT
Other Contributors
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Advisor
Charles G. Sodini and Martin Choquette.
Terms of use
Metadata
Show full item recordAbstract
The arrival of photons at a given location is a Poisson process with an associated shot noise which rises with the square root of the number of photons received. An analog-to-digital converter (ADC) with a square root transfer function can quantize photonic signals with LSB size kept constant with respect to the photon shot noise. In imaging applications, this can greatly reduce the number of bits needed to characterize a signal compared to a linear ADC without detrimental effects to image quality. Such a device, based on the Analogic MuSIC chip, was designed and tested for the needs of a medical computed tomography (CT) device. The experimental setup increases the MuSIC sampling frequency from 3kHz to 7kHz, while reducing the amount of data necessary for reconstruction. A constant quantization noise to photon shot noise ratio acceptable for CT is maintained by sizing each LSB to be one half the rms noise level. Results show an INL of 2.5 LSB, which is reduced to 0.27 LSB after a correction scheme.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (p. 81-82).
Date issued
2010Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.