Self-supervised Noise-aware Network for Dynamic Rubidium-82 Cardiac PET Image Denoising-Reference-Cited by-同舟云学术

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Self-supervised Noise-aware Network for Dynamic Rubidium-82 Cardiac PET Image Denoising

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:

Xie H.¹,Guo L.¹,Guo X.¹,Liu Q.¹,Zhou B.¹,Chen X.¹,Wang G.²,Sinusas A. J.¹,Liu C.¹

Affiliation:

1. Yale University,Radiology & Biomedical Imaging & Biomedical Engineering & Internal Medicine,New Haven,Connecticut,United States of America

2. Rensselaer Polytechnic Institute,Biomedical Engineering,Troy,New York,United States of America

Funder

National Institutes of Health

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10337770/10337807/10338703.pdf?arnumber=10338703

Reference5 articles.

1. Dynamic cardiac PET imaging: Technological improvements advancing future cardiac health

2. Unified Noise-Aware Network for Low-Count PET Denoising With Varying Count Levels

3. PET image denoising using unsupervised deep learning

4. Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results;Tarvainen

5. Segmentation-Free PVC for Cardiac SPECT Using a Densely-Connected Multi-Dimensional Dynamic Network

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