Weakly Supervised Breast Lesion Detection in Dynamic Contrast-Enhanced MRI-Reference-Cited by-同舟云学术

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Weakly Supervised Breast Lesion Detection in Dynamic Contrast-Enhanced MRI

Published:2023-05-30 Issue:4 Volume:36 Page:1553-1564
ISSN:1618-727X
Container-title:Journal of Digital Imaging
language:en
Short-container-title:J Digit Imaging

Author:

Sun Rong,Wei Chuanling,Jiang Zhuoyun,Huang Gang,Xie Yuanzhong,Nie Shengdong^ORCID

Funder

National Natural Science Foundation of China

Science and Technology Innovation Plan Of Shanghai Science and Technology Commission

Natural Science Foundation of Shanghai

Shanghai Key Laboratory of Molecular Imaging

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

https://link.springer.com/content/pdf/10.1007/s10278-023-00846-5.pdf

Reference39 articles.

1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F: Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Ca-a Cancer Journal for Clinicians 71(3):209-249, 2021 https://doi.org/10.3322/caac.21660

2. Chan HP, Samala RK, Hadjiiski LM: CAD and AI for breast cancer-recent development and challenges. Br J Radiol 93(1108), 2020 https://doi.org/10.1259/bjr.20190580

3. Zhang Y, Chen J-H, Lin Y, Chan S, Zhou J, Chow D, Chang P, Kwong T, Yeh D-C, Wang X, Parajuli R, Mehta RS, Wang M, Su M-Y: Prediction of breast cancer molecular subtypes on DCE-MRI using convolutional neural network with transfer learning between two centers. Eur Radiol 31(4): 2559-2567, 2020 https://doi.org/10.1007/s00330-020-07274-x

4. Zhu Z, Albadawy E, Saha A, Zhang J, Harowicz MR, Mazurowski MA: Deep learning for identifying radiogenomic associations in breast cancer. Comput Biol Med 109:85-90, 2019 https://doi.org/10.1016/j.compbiomed.2019.04.018

5. Ha R, Mutasa S, Karcich J, Gupta N, Van Sant EP, Nemer J, Sun M, Chang P, Liu MZ, Jambawalikar S: Predicting breast cancer molecular subtype with MRI dataset utilizing convolutional neural network algorithm. J Digit Imaging 32(2):276-282, 2019 https://doi.org/10.1007/s10278-019-00179-2

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