Evaluation of image quality of a deep learning image reconstruction algorithm

Meghan Yue; Jie Tang; Brian E. Nett; Jiang Hsieh; Roy Nilsen; Jiahua Fan

doi:10.1117/12.2534961

28 May 2019 Evaluation of image quality of a deep learning image reconstruction algorithm

Meghan Yue, Jie Tang, Brian E. Nett, Jiang Hsieh, Roy Nilsen, Jiahua Fan

Proceedings Volume 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine; 110722X (2019) https://doi.org/10.1117/12.2534961
Event: Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, Philadelphia, United States

Abstract

The iterative reconstruction methods ASiR and ASiR-V have been accepted by hundreds of sites as their standard of care for a variety of protocols and applications. While the reduction in noise has been significant some readers have a preference for the classic image appearance. To maintain the classic image appearance of FBP at the same dose levels used for the standard of care with ASiR-V we introduce, Deep Learning Image Reconstruction (DLIR), a technique using artificial neural networks. This paper demonstrates that DLIR can maintain or improve upon the performance of the conventional iterative reconstruction algorithm (ASiR-V) in terms of low contrast detectability, noise, and spatial resolution.

Citation Download Citation

Meghan Yue, Jie Tang, Brian E. Nett, Jiang Hsieh, Roy Nilsen, and Jiahua Fan "Evaluation of image quality of a deep learning image reconstruction algorithm", Proc. SPIE 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 110722X (28 May 2019); https://doi.org/10.1117/12.2534961

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