Segmented separable footprint projector for digital breast tomosynthesis and its application for subpixel reconstruction-Reference-Cited by-同舟云学术

Segmented separable footprint projector for digital breast tomosynthesis and its application for subpixel reconstruction

Published:2017-03 Issue:3 Volume:44 Page:986-1001
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Zheng Jiabei¹²,Fessler Jeffrey A.¹²,Chan Heang-Ping¹

Affiliation:

1. Department of Radiology; 1500 E Medical Center Dr; Ann Arbor MI 48109 USA

2. Department of Electrical and Computer Engineering; 1301 Beal Ave; Ann Arbor MI 48109 USA

Funder

National Institutes of Health

Publisher

Wiley

Subject

General Medicine

Reference41 articles.

1. Research digital tomosynthesis mammography: detection of T1 invasive breast carcinomas not diagnosed by conventional breast imaging or physical exam;Helvie;RSNA Program Book,2008

2. Digital breast tomosynthesis: initial experience in 98 women with abnormal digital screening mammography;Poplack;Am J Roentgenol,2007

3. Clinical performance of breast tomosynthesis as a function of radiologist experience level, IWDM 2008 -;Smith;Lect Notes Comput Sci,2008

4. Clinical performance of digital breast tomosynthesis versus full-field digital mammography: preliminary results, IWDM 2008 -;Gennaro;Lect Notes Comput Sci,2008

5. Digital breast tomosynthesis mammography: successsful assessment of benign and malignant microcalcifications;Helvie;RSNA Program Book,2009

Cited by 8 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. X-ray source motion blur modeling and deblurring with generative diffusion for digital breast tomosynthesis;Physics in Medicine & Biology;2024-05-14

2. Super-Resolution in Low Dose X-ray CT via Focal Spot Mitigation With Generative Diffusion Networks;IEEE Transactions on Computational Imaging;2024

3. Deep Convolutional Neural Network With Adversarial Training for Denoising Digital Breast Tomosynthesis Images;IEEE Transactions on Medical Imaging;2021-07

4. Digital breast tomosynthesis denoising using deep convolutional neural network: effects of dose level of training target images;Medical Imaging 2021: Physics of Medical Imaging;2021-02-15

5. Deep convolutional neural network denoising for digital breast tomosynthesis reconstruction;Medical Imaging 2020: Physics of Medical Imaging;2020-03-16