Share Email Print

Proceedings Paper

Noise balance in pre-reconstruction decomposition in spectral CT
Author(s): Xiaolan Wang; Yu Zou
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Spectral CT requires two or more independent measurements for each ray path in order to extract complete energydependent information of the object attenuation. The number of required measurements is equivalent to the number of independent basis functions needed to describe the attenuation of the imaged objects. For example, two independent measurements are sufficient if only photoelectric absorption and Compton scattering are dominating. If additional Kedge( s) is present in the energy range of interest, more than two measurements are necessary. In this study, we present a pre-reconstruction decomposition method that utilizes spectral data redundancy to improve image quality. We assume projection data are acquired with an M-energy-bin photon counting detector that generates M independent measurements, and the attenuation of the objects can be described with N (M < M) basis functions. The method addresses un-balanced noise level of data from different energy bins of the photon counting detector. During a CT scan, with the non-uniform attenuation of a typical patient, spectral shape and beam intensity can change drastically from detector to detector, from view to view. As a consequence, a detector unit is subject to significantly varying incident x-ray spectra. Hardware adjustment approaches are limited by current detector and mechanical technology, and almost not possible in a typical clinical CT scan with e.g., 1800 views / 0.5 s. Our method applies adaptive noise balance weighting to data acquired from different energy bins, post data acquisition and prior data decomposition. The results show substantially improved quality in spectral images reconstructed from photon counting detector data.

Paper Details

Date Published: 19 March 2014
PDF: 5 pages
Proc. SPIE 9033, Medical Imaging 2014: Physics of Medical Imaging, 90333K (19 March 2014); doi: 10.1117/12.2042175
Show Author Affiliations
Xiaolan Wang, Toshiba Medical Research Institute (United States)
Yu Zou, Toshiba Medical Research Institute (United States)

Published in SPIE Proceedings Vol. 9033:
Medical Imaging 2014: Physics of Medical Imaging
Bruce R. Whiting; Christoph Hoeschen, Editor(s)

© SPIE. Terms of Use
Back to Top