Breast Cancer Segmentation From Ultrasound Images Using Multiscale Cascaded Convolution With Residual Attention-Based Double Decoder Network-Reference-Cited by-同舟云学术

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Breast Cancer Segmentation From Ultrasound Images Using Multiscale Cascaded Convolution With Residual Attention-Based Double Decoder Network

Published:2024 Issue: Volume:12 Page:107888-107902
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Umer Muhammad Junaid¹^ORCID,Sharif Muhammad Irfan²^ORCID,Kim Jungeun³^ORCID

Affiliation:

1. Department of Computer Science, COMSATS University Islamabad, Wah Campus, Wah Cantt, Pakistan

2. Department of Information Sciences, University of Education Lahore, Jauharabad Campus, Jauharabad, Pakistan

3. Department of Software, Kongju National University, Cheonan, South Korea

Funder

Technology Development Program of MSS

Research Grant of Kongju National University in 2024

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10599427.pdf?arnumber=10599427

Reference53 articles.

1. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

2. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

3. Survey of deep learning in breast cancer image analysis

4. Boosting Breast Cancer Detection Using Convolutional Neural Network

5. Breast Cancer Screening Among Childhood Cancer Survivors Treated Without Chest Radiation: Clinical Benefits and Cost-Effectiveness

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1. Breast lesions segmentation from ultrasound images using DeepLabV3 + model with channel and spatial attention mechanism;Discover Sustainability;2024-08-29

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