Application of Tikhonov regularization to the restoration of phase contrast images

Zhongxing Zhou; Qingzhen Zhu; Feng Gao; Huijuan Zhao; Lixin Zhang

doi:10.1117/12.907577

28 February 2012 Application of Tikhonov regularization to the restoration of phase contrast images

Zhongxing Zhou, Qingzhen Zhu, Feng Gao, Huijuan Zhao, Lixin Zhang

Proceedings Volume 8214, Advanced Biomedical and Clinical Diagnostic Systems X; 82141E (2012) https://doi.org/10.1117/12.907577
Event: SPIE BiOS, 2012, San Francisco, California, United States

Abstract

New X-ray phase contrast imaging techniques without using synchrotron radiation confront a common problem from the negative effects of finite source sizes and limited spatial resolution. These negative effects swamp the fine phase contrast fringes and make them almost undetectable. In order to alleviate this problem, deconvolution procedures should be applied to the x-ray phase contrast images. In this study, four different deconvolution techniques were applied to experimental phase contrast images of a simple geometric phantom, including Weiner deconvolution method and Tikhonov regularization techniques with their Tikhonov matrix separately set as identity matrix, first order difference operator and second order difference operator. According to the free space propagation x-ray phase contrast imaging system, the source-to-sample distance (SS) of 200cm or 180cm was used with corresponding sample-to-detector distance (SD) of 20cm or 40cm. Image contrasts of 9.8%, 52.7%, 27.6% and 31.5% were separately obtained corresponding to above mentioned four techniques with SS/SD=200cm/20cm. For the second system setting (SS/SD=180cm/40cm), image contrasts of 11.9%, 112.8%, 66.3% and 76.5% were obtained separately. The Tikhonov regularization technique with Tikhonov matrix chosen as identity matrix obtains the highest contrast among all techniques. However, under this case, most noticeable artifacts and noise were introduced simultaneously. With full consideration on noise and artifacts, the Tikhonov matrix of second order difference operator will be the best choice for Tikhonov regularization method.

Citation Download Citation

Zhongxing Zhou, Qingzhen Zhu, Feng Gao, Huijuan Zhao, and Lixin Zhang "Application of Tikhonov regularization to the restoration of phase contrast images", Proc. SPIE 8214, Advanced Biomedical and Clinical Diagnostic Systems X, 82141E (28 February 2012); https://doi.org/10.1117/12.907577

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