Evaluation of image quality of a deep learning image reconstruction algorithm
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.
- Publication:
-
15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine
- Pub Date:
- May 2019
- DOI:
- 10.1117/12.2534961
- Bibcode:
- 2019SPIE11072E..2XY