Statistically optimal image reconstruction in propagation-based phase-contrast tomography

Mark A. Anastasio; Cheng-Ying Chou; Yin Huang; Daxin Shi

doi:10.1117/12.681301

7 September 2006 Statistically optimal image reconstruction in propagation-based phase-contrast tomography

Mark A. Anastasio, Cheng-Ying Chou, Yin Huang, Daxin Shi

Proceedings Volume 6318, Developments in X-Ray Tomography V; 63180U (2006) https://doi.org/10.1117/12.681301
Event: SPIE Optics + Photonics, 2006, San Diego, California, United States

Abstract

Propagation-based phase-contrast tomography is a coherent imaging method that seeks to reconstruct the three-dimensional complex-valued refractive index distribution of an object. Measurements of the transmitted wavefield intensities on two parallel detector-planes at each tomographic view angle are utilized to determine the wavefield's complex amplitude, which represent the projection data utilized for tomographic reconstruction. The mathematical formulas employed to determine the complex amplitude contain Fourier domain singularities that can result in greatly amplified noise levels in the reconstructed images. In this article, statistically optimal reconstruction methods that employ multiple (>2) detector-planes are developed that mitigate the noise amplification effects due to singularities in the reconstruction formulas. These reconstruction methods permit exploitation of statistically complementary information in a collection of in-line holographic measurement data, resulting in images that can have dramatically reduced noise levels. Computer-simulation studies are conducted to demonstrate and investigate quantitatively the developed reconstruction methods.

Citation Download Citation

Mark A. Anastasio, Cheng-Ying Chou, Yin Huang, and Daxin Shi "Statistically optimal image reconstruction in propagation-based phase-contrast tomography", Proc. SPIE 6318, Developments in X-Ray Tomography V, 63180U (7 September 2006); https://doi.org/10.1117/12.681301

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