Deep learning scatter estimation for breast tomosynthesis based on a realistic compressed breast shape model in the CC view-Reference-Cited by-同舟云学术

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Deep learning scatter estimation for breast tomosynthesis based on a realistic compressed breast shape model in the CC view

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:

Pinto Marta C.,Michielsen Koen,Rodríguez-Ruiz Alejandro,Bianiazan Ramyar,Kappler Steffen,Sechopoulos Ioannis

Publisher

SPIE

Reference14 articles.

1. Evaluation of scatter effects on image quality for breast tomosynthesis

2. Estimation of scattered radiation in digital breast tomosynthesis

3. X-ray scatter correction in breast tomosynthesis with a precomputed scatter map library

4. Scatter correction with deep learning approach for contrast enhanced digital breast tomosynthesis (CEDBT) in both cranio-caudal (CC) view and mediolateral oblique (MLO) view;Duan,2020

Cited by 3 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. Breast shape-specific subtraction for improved contrast-enhanced mammography imaging;Medical Imaging 2024: Physics of Medical Imaging;2024-04-01

2. Deep-learning convolutional neural network-based scatter correction for contrast enhanced digital breast tomosynthesis in both cranio-caudal and mediolateral-oblique views;Journal of Medical Imaging;2023-03-15

3. Generative compressed breast shape model for digital mammography and digital breast tomosynthesis;Medical Physics;2022-12-10

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