Application of learned ideal observers for estimating task-based performance bounds for computed imaging systems

Authors

Kaiyan Li, University of Illinois
Umberto Villa, University of Texas at Austin
Hua Li, Washington University School of Medicine in St. Louis
Mark A. Anastasio, University of Illinois

Journal

Journal of Medical Imaging

Publication Date

3-20-2024

Volume

11

Issue

2

First Page

026002

Document Type

Open Access Publication

DOI

10.1117/1.JMI.11.2.026002

Rights and Permissions

Kaiyan Li, Umberto Villa, Hua Li, Mark A. Anastasio, "Application of learned ideal observers for estimating task-based performance bounds for computed imaging systems," J. Med. Imag. 11(2) 026002 (20 March 2024) https://doi.org/10.1117/1.JMI.11.2.026002 CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Recommended Citation

Li, Kaiyan; Villa, Umberto; Li, Hua; and Anastasio, Mark A., "Application of learned ideal observers for estimating task-based performance bounds for computed imaging systems." Journal of Medical Imaging. 11, 2. 026002 (2024).
https://digitalcommons.wustl.edu/oa_4/3808

Department

ICTS (Institute of Clinical and Translational Sciences)

Additional Links

Supplemental material is available for this article at publisher site.