Breast Density Classification to Aid Clinical Workflow in Breast Cancer Detection Using Deep Learning Network-Reference-Cited by-同舟云学术

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Breast Density Classification to Aid Clinical Workflow in Breast Cancer Detection Using Deep Learning Network

Published:2023-10-31 Issue: Volume: Page:
ISSN:
Container-title:TENCON 2023 - 2023 IEEE Region 10 Conference (TENCON)
language:
Short-container-title:

Author:

Saran K B¹,Sreelekha G¹,Sunitha V C²

Affiliation:

1. National Institute of Technology,Calicut

2. Jawaharlal Institute of Postgraduate Medical Education and Research,Pondicherry

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10322307/10322308/10322346.pdf?arnumber=10322346

Reference22 articles.

1. Curated Breast Imaging Subset of Digital Database for Screening Mammography (CBIS-DDSM) (Version 1) [Data set;sawyer-lee;The Cancer Imaging Archive,2016

2. Determination of mammographic breast density using a deep convolutional neural network;alexander;The British Journal of Radiology,2019

3. INbreast

4. Mammo-graphic Image Analysis Society (MIAS) database v1.21;suckling;Apollo -University of Cambridge Repository,2015

5. Architectural distortion detection in digital breast tomosynthesis with adaptive receptive field and adaptive convolution kernel shape;yue;Medical Imaging 2021 Computer-Aided Diagnosis,2021

Cited by 1 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. Attention-Based Ensemble Network for Effective Breast Cancer Classification over Benchmarks;Technologies;2024-01-23

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