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Journal of Medical Imaging

Noise properties and task-based evaluation of diffraction-enhanced imaging
Author(s): Jovan G. Brankov; Alejandro Saiz-Herranz; Miles N. Wernick
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Paper Abstract

Diffraction-enhanced imaging (DEI) is an emerging x-ray imaging method that simultaneously yields x-ray attenuation and refraction images and holds great promise for soft-tissue imaging. The DEI has been mainly studied using synchrotron sources, but efforts have been made to transition the technology to more practical implementations using conventional x-ray sources. The main technical challenge of this transition lies in the relatively lower x-ray flux obtained from conventional sources, leading to photon-limited data contaminated by Poisson noise. Several issues that must be understood in order to design and optimize DEI imaging systems with respect to noise performance are addressed. Specifically, we: (a) develop equations describing the noise properties of DEI images, (b) derive the conditions under which the DEI algorithm is statistically optimal, (c) characterize the imaging performance that can be obtained as measured by task-based metrics, and (d) consider image-processing steps that may be employed to mitigate noise effects.

Paper Details

Date Published: 11 November 2014
PDF: 11 pages
J. Med. Img. 1(3) 033503 doi: 10.1117/1.JMI.1.3.033503
Published in: Journal of Medical Imaging Volume 1, Issue 3
Show Author Affiliations
Jovan G. Brankov, Illinois Institute of Technology (United States)
Alejandro Saiz-Herranz, Illinois Institute of Technology (United States)
Miles N. Wernick, Illinois Institute of Technology (United States)


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