Integration of ultrasound and mammogram for multimodal classification of breast cancer using hybrid residual neural network and machine learning-Reference-Cited by-同舟云学术

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Integration of ultrasound and mammogram for multimodal classification of breast cancer using hybrid residual neural network and machine learning

Published:2024-05 Issue: Volume:145 Page:104987
ISSN:0262-8856
Container-title:Image and Vision Computing
language:en
Short-container-title:Image and Vision Computing

Author:

Atrey Kushangi,Singh Bikesh Kumar,Bodhey Narendra Kuber

Publisher

Elsevier BV

Reference35 articles.

1. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries;Bray;CA Cancer J. Clin.,2018

2. AW3M: an auto-weighting and recovery framework for breast cancer diagnosis using multi-modal ultrasound;Huang;Med. Image Anal.,2021

3. A novel deep learning based framework for the detection and classification of breast cancer using transfer learning;Khan;Pattern Recogn. Lett.,2019

4. A new nested ensemble technique for automated diagnosis of breast cancer;Abdar;Pattern Recogn. Lett.,2020

5. Breast cancer detection and validation using dual modality imaging;Atrey,2020

Cited by 2 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. WoodGLNet: a multi-scale network integrating global and local information for real-time classification of wood images;Journal of Real-Time Image Processing;2024-08

2. Machine Learning for Early Breast Cancer Detection;Journal of Engineering and Science in Medical Diagnostics and Therapy;2024-07-26

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