Deep convolutional neural network denoising for digital breast tomosynthesis reconstruction-Reference-Cited by-同舟云学术

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Deep convolutional neural network denoising for digital breast tomosynthesis reconstruction

Published:2020-03-16 Issue: Volume: Page:
ISSN:
Container-title:Medical Imaging 2020: Physics of Medical Imaging
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Author:

Gao Mingjie,Samala Ravi K.,Fessler Jeffrey A.,Chan Heang-Ping

Publisher

SPIE

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Recent developments in denoising medical images using deep learning: An overview of models, techniques, and challenges;Micron;2024-05

2. Model-based deep CNN-regularized reconstruction for digital breast tomosynthesis with a task-based CNN image assessment approach;Physics in Medicine & Biology;2023-12-13

3. Deep learning based tomosynthesis denoising: a bias investigation across different breast types;Journal of Medical Imaging;2023-12-07

4. Deep learning denoising of digital breast tomosynthesis: Observer performance study of the effect on detection of microcalcifications in breast phantom images;Medical Physics;2023-05-05

5. Imposing noise correlation fidelity on digital breast tomosynthesis restoration through deep learning techniques;16th International Workshop on Breast Imaging (IWBI2022);2022-07-13

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