Automated Breast Cancer Detection and Classification in Full Field Digital Mammograms Using Two Full and Cropped Detection Paths Approach-Reference-Cited by-同舟云学术

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Automated Breast Cancer Detection and Classification in Full Field Digital Mammograms Using Two Full and Cropped Detection Paths Approach

Published:2021 Issue: Volume:9 Page:116898-116913
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Hamed Ghada,Marey Mohammed,Amin Safaa Elsayed,Tolba Mohamed F.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9312710/09515973.pdf?arnumber=9515973

Cited by 30 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. Low-Cost Early Detection Device for Breast Cancer based on Skin Surface Temperature;IT Journal Research and Development;2024-07-23

2. Multimodal breast cancer hybrid explainable computer-aided diagnosis using medical mammograms and ultrasound Images;Biocybernetics and Biomedical Engineering;2024-07

3. Breast cancer diagnosis model using stacked autoencoder with particle swarm optimization;Ain Shams Engineering Journal;2024-06

4. Denoising and segmentation in medical image analysis: A comprehensive review on machine learning and deep learning approaches;Multimedia Tools and Applications;2024-05-17

5. Reinforcement learning (RL)-based semantic segmentation and attention based backpropagation convolutional neural network (ABB-CNN) for breast cancer identification and classification using mammogram images;Neural Computing and Applications;2024-05-11

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