Pipeline for effective denoising of digital mammography and digital breast tomosynthesis-Reference-Cited by-同舟云学术

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Pipeline for effective denoising of digital mammography and digital breast tomosynthesis

Published:2017-03-09 Issue: Volume: Page:
ISSN:0277-786X
Container-title:Medical Imaging 2017: Physics of Medical Imaging
language:
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Author:

Borges Lucas R.¹,Bakic Predrag R.²,Foi Alessandro²,Maidment Andrew D. A.²,Vieira Marcelo A. C.¹

Affiliation:

1. Univ. de São Paulo (Brazil)

2. Univ. of Pennsylvania (United States)

Publisher

SPIE

Cited by 18 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. Evaluating an image restoration pipeline for digital mammography across varied radiation exposures and microcalcification sizes using model observer analysis;17th International Workshop on Breast Imaging (IWBI 2024);2024-05-29

2. Impact of loss functions on the performance of a deep neural network designed to restore low-dose digital mammography;Artificial Intelligence in Medicine;2023-08

3. A denoising model based on multi-agent reinforcement learning with data transformation for digital tomosynthesis;Physics in Medicine & Biology;2023-06-12

4. Denoising digital breast tomosynthesis projections using deep learning with synthetic data as training set;Journal of Medical Imaging;2023-05-22

5. A benchmark of denoising digital breast tomosynthesis in projection domain: neural network-based and traditional methods;Medical Imaging 2022: Image Processing;2022-04-04

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