Spectrum estimation based on a parametric physical model for CT

Shaojie Chang; Xi Chen; Yang Li; Xuanqin Mou

doi:10.1117/12.2548002

19 May 2020 Spectrum estimation based on a parametric physical model for CT

Shaojie Chang, Xi Chen, Yang Li, Xuanqin Mou

Proceedings Volume 11312, Medical Imaging 2020: Physics of Medical Imaging; 113122P (2020) https://doi.org/10.1117/12.2548002
Event: SPIE Medical Imaging, 2020, Houston, Texas, United States

Abstract

X-ray spectrum plays an essential role in CT applications. Since it is difficult to measure x-ray spectrum directly in practice, x-ray spectrum is always indirectly obtained by using transmission measurements through a calibration phantom of known thickness and materials. These methods are independent of CT image reconstruction and bring extra cost. In this study, we propose a parametric physical model based spectrum estimation algorithm for CT. First, a physical model contains six parameters is proposed to represent the x-ray spectrum, which is derived from the x-ray imaging physics. Second, a template image contains different material components can be obtained by segmenting CT reconstructed images with a simple method. And the estimated projection can be calculated by reprojecting the template image with the proposed spectrum model. Finally, the six parameters expressing the spectrum can be solved by minimizing the error between the estimated projection and real measurements. The effectiveness of the proposed method has been validated on the simulated data. Experimental results demonstrate the proposed method can estimate the accurate spectra at low and high energies and provide a good reconstruction of characteristic radiations.

Citation Download Citation

Shaojie Chang, Xi Chen, Yang Li, and Xuanqin Mou "Spectrum estimation based on a parametric physical model for CT", Proc. SPIE 11312, Medical Imaging 2020: Physics of Medical Imaging, 113122P (19 May 2020); https://doi.org/10.1117/12.2548002

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available