Photon counting detector Cross talk model and optimizing information in spectral CT

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Abstract/Contents

Abstract
Spectral computed tomography (CT) provides additional information about energy dependent object attenuation and material composition that can be diagnostically useful. Conventional CT images display the linear attenuation coefficient (often represented in Hounsfield units HU) of the material. This value represents the tissue property in the voxel but is affected by the x-ray spectrum. Different materials in a conventional image could have similar HU due to its effective energy set inherently and potentially non-optimally by the system based on spectrum used. In contrast, x-ray spectral information can be used to reconstruct images solely of object properties (i.e., independent of energy) and can, in principle, be free of beam hardening artifacts. Macovski and Alvarez introduced a theoretical framework for material decomposition. Material decomposition allows separation of materials in object into two (or more) basis functions based on spectral acquisition of x-ray transmission measurement. This in turn allows physics based material segmentation, and the possibility of quantitative CT imaging and representation of effective energy images at desired energies where contrast between materials are optimal. There has been increasing interest in the x-ray and CT research community to utilize energy discriminating photon counting detectors (PCD), previously used in nuclear medicine and other disciplines, but PCD suffers from several algorithmic and detector challenges. This work attempts to explore some of the challenges in PCD for x-ray and CT imaging. A material decomposition algorithm for an over-determined multi-bin PCD system that provides a practical balance between speed, accuracy and noise properties for such an overdetermined system is a challenge. This work also studies and compares methods of producing "conventional" looking CT images using multi-bin PCD measurements. Count rate limitation and spatio-energetic cross-talk between signals in PCD degrade measurements. Smaller detector pixels may be preferred so each detector pixel can operate below flux saturation region. However, smaller detector pixels suffer from more severe spectral degradation and strong cross-talk between pixels. This work derives a correlation model for multi-counting in PCD due to spatio-energetic cross talk caused by charge sharing, scatter and fluorescence in the detector. The study also presents comparison of frequency dependent detector performance for different CdTe pixel sizes for a spectral task and effective monoenergetic imaging. We find that spectral degradation and spatio-energetic cross talk affect smaller pixels more severely for spectral task than for effective monoenergetic tasks. As an auxiliary to the study, this work also presents the impact electronic noise in PCD can have in imaging applications. We find that electronic noise for the simulated CdTe detector at the lowest can have up to 15-25% degradation in spectral imaging applications while effective energy imaging is relatively immune to electronic noise.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2018
Issuance monographic
Language English

Creators/Contributors

Associated with Rajbhandary, Paurakh Lal
Associated with Stanford University, Department of Electrical Engineering.
Primary advisor Pelc, Norbert J
Thesis advisor Pelc, Norbert J
Thesis advisor Hsieh, Scott
Thesis advisor Nishimura, Dwight George
Thesis advisor Pauly, John (John M.)
Advisor Hsieh, Scott
Advisor Nishimura, Dwight George
Advisor Pauly, John (John M.)

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Paurakh Lal Rajbhandary.
Note Submitted to the Department of Electrical Engineering.
Thesis Thesis (Ph.D.)--Stanford University, 2018.
Location electronic resource

Access conditions

Copyright
© 2018 by Paurakh Lal Rajbhandary
License
This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).

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