Assessment of training strategies for convolutional neural network to restore low-dose digital breast tomosynthesis projections-Reference-Cited by-同舟云学术

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Assessment of training strategies for convolutional neural network to restore low-dose digital breast tomosynthesis projections

Published:2022-04-04 Issue: Volume: Page:
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Container-title:Medical Imaging 2022: Physics of Medical Imaging
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Author:

de Barros Vimieiro Rodrigo,Rodrigues Borges Lucas,Barufaldi Bruno,Maidment Andrew D. A.,Wang Ge,Andrade da Costa Vieira Marcelo

Publisher

SPIE

Reference29 articles.

1. Deep learning on image denoising: An overview

2. Denoising digital breast tomosynthesis projections using convolutional neural networks;de Araújo,2021

3. Han, M. and Baek, J., “Low-dose CT denoising via CNN with an observer loss function,” in [Medical Imaging 2021: Physics of Medical Imaging], 11595, 1159544, International Society for Optics and Photonics (2021).

4. Deep neural networks-based denoising models for CT imaging and their efficacy;Prabhat,2021

5. Deep convolutional neural network denoising for digital breast tomosynthesis reconstruction

Cited by 1 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. 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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