Validation of a mammographic image quality modification algorithm using 3D-printed breast phantoms
Author:
Affiliation:
1. Radboud University Medical Center, Department of Medical Imaging, Nijmegen
2. Royal Surrey NHS Foundation Trust, National Coordinating Centre for the Physics of Mammography, Guil
3. Dutch Expert Centre for Screening (LRCB), Nijmegen
Publisher
SPIE-Intl Soc Optical Eng
Subject
Radiology, Nuclear Medicine and imaging
Cited by 6 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. Capability and reliability of deep learning models to make density predictions on low-dose mammograms;Journal of Medical Imaging;2024-08-06
2. Creation of simulated mammography data to supplement machine learning training datasets;17th International Workshop on Breast Imaging (IWBI 2024);2024-05-29
3. Breast density prediction from low and standard dose mammograms using deep learning: effect of image resolution and model training approach on prediction quality;Biomedical Physics & Engineering Express;2024-05-15
4. Physical and digital phantoms for 2D and 3D x-ray breast imaging: Review on the state-of-the-art and future prospects;Radiation Physics and Chemistry;2023-03
5. 3D and 4D Printing in the Fight against Breast Cancer;Biosensors;2022-07-26
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