Synthesize monochromatic images in spectral CT by dual-domain deep learning

Chuqing Feng; Zhiqiang Chen; Kejun Kang; Yuxiang Xing

doi:10.1117/12.2534921

28 May 2019 Synthesize monochromatic images in spectral CT by dual-domain deep learning

Chuqing Feng, Zhiqiang Chen, Kejun Kang, Yuxiang Xing

Proceedings Volume 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine; 1107229 (2019) https://doi.org/10.1117/12.2534921
Event: Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, Philadelphia, United States

Abstract

Spectral computed tomography (CT) with photon counting detectors (PCDs) can collect photons by setting different energy bins. It is well acknowledged that PCD-based spectral CT has great potential for lowering radiation dose and improve material discrimination. One critical processing in spectral CT is energy spectrum modelling or spectral information decomposition. In this work, we proposed a dual-domain deep learning (DDDL) method to calibrate a spectral CT system by a neural network. Without explicit energy spectrum and detector response model, we train a neural network to implicitly define the non-linear relationship in spectral CT. Virtual monochromatic attenuation maps are synthesized directly from polychromatic projections. Simulation and real experimental results verified the feasibilities and accuracies of the proposed method.

Citation Download Citation

Chuqing Feng, Zhiqiang Chen, Kejun Kang, and Yuxiang Xing "Synthesize monochromatic images in spectral CT by dual-domain deep learning", Proc. SPIE 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 1107229 (28 May 2019); https://doi.org/10.1117/12.2534921

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