A Feasibility Study of Domain-aware Deep Learning Ideal Model Observer-Reference-Cited by-同舟云学术

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A Feasibility Study of Domain-aware Deep Learning Ideal Model Observer

Published:2023-11-04 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)
language:
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Author:

Bogdanovic N.¹,Abbey C. K.²,Brankov J. G.¹

Affiliation:

1. Illinois Institute of Technology,Electrical and Computer Engineering,Chicago,Illinois,United States of America

2. University of California Santa Barbara,Department of Psychological and Brain Sciences,Santa Barbara,California,United States of America

Funder

Health

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10337770/10337807/10338058.pdf?arnumber=10338058

Reference5 articles.

1. Unified SNR analysis of medical imaging systems

2. Image quality, the ideal observer, and human performance of radiologic decision tasks

3. Approximating the Ideal Observer for Joint Signal Detection and Localization Tasks by use of Supervised Learning Methods

4. Evaluation of CNN as anthropomorphic model observer

5. High human-observer efficiency for forced-localization tasks in correlated noise

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