Multi-slice and multi-frame image reconstruction by predictive compressed sensing

Jun Zhang; Jun Wang; Guangwu Xu; Jean-Baptiste Thibault

doi:10.1117/12.911150

24 February 2012 Multi-slice and multi-frame image reconstruction by predictive compressed sensing

Jun Zhang, Jun Wang, Guangwu Xu, Jean-Baptiste Thibault

Proceedings Volume 8314, Medical Imaging 2012: Image Processing; 83144M (2012) https://doi.org/10.1117/12.911150
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

In this paper, we describe a prediction based compressed-sensing approach for multi-slice (same time, different locations) or multi-frame (same location, different time) CT image reconstruction. In this approach, the second slice/frame of a pair of consecutive slices/frames is reconstructed through reconstructing the prediction error image between the first and second slice/frame, using compressed-sensing. This approach exploits the inter-slice/inter-frame correlation and the higher degree of sparsity of the prediction error image to achieve more efficient image reconstruction, i.e., fewer projections for the same image quality or higher image quality for the same number of projections. The efficacy of our approach is demonstrated through simulation results.

Citation Download Citation

Jun Zhang, Jun Wang, Guangwu Xu, and Jean-Baptiste Thibault "Multi-slice and multi-frame image reconstruction by predictive compressed sensing", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83144M (24 February 2012); https://doi.org/10.1117/12.911150

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