Convolutional Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening for Vietnamese patients

Author:

Hanh Bui My1,Linh Le Tuan1,Cuong Nguyen Ngoc1,Nguyen Thanh Binh1,Doan Luu Tien1,Le Chung Duy1,Giao Vu Tat1,Ngo Thi Ly Ly1,Hoang Thi Hong Xuyen1,Thang Nguyen Duc2,Anh Nguyen Tu2,Dan Nguyen Duc2,Dung Nguyen Viet3,Duc Tran Vinh3,Nguyen Quang H.3,Nguyen Anh4,Phuong Nguyen Hoang2

Affiliation:

1. Hanoi Medical University Hospital, Hanoi Medical University Hospital, Hanoi, Vietnam

2. Thang Long University, Hanoi, Vietnam

3. Hanoi University of Science and Technology, Hanoi, Vietnam

4. Auburn University, Auburn, Alabama, USA

Funder

Thang Long University and the Hanoi Medical

Publisher

Informa UK Limited

Subject

Artificial Intelligence

Reference20 articles.

1. Deep Transfer Learning-Based Breast Cancer Detection and Classification Model Using Photoacoustic Multimodal Images

2. Mammographic mass classification according to Bi‐RADS lexicon

3. de Chaumont, F., S. Dallongeville, N. Chenouard, H. Herve, S. Pop, T. Provoost, V. Meas-Yedid, P. Pankajakshan, T. Lecomte, and Y. Montagner. 2019. ICY: An open community platform for Bioimage Informatics. http://icy.bioimageanalysis.org/.

4. Geras, K. J., S. Wolfson, Y. Shen, N. Wu, S. G. Kim, E. Kim, L. Heacock, U. Parikh, L. Moy, and K. Cho. 2018. High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks. arXiv:1703.07047v3 [cs.CV] 28 June 2018.

5. The global cancer observatory. March, 2021. https://gco.iarc.fr/today/data/factsheets/populations/704-viet-nam-fact-sheets.pdf.

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. A Classification System of Mammograms Based on Convolutional Neural Networks;Studies in Systems, Decision and Control;2024

2. Transfer learning for deep neural networks-based classification of breast cancer X-ray images;Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization;2023-11-18

3. Convolutional Neural Networks Based Classification of Mammograms;Proceedings of the 2023 International Conference on Advances in Computing Research (ACR’23);2023

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