Cross-Parametric Generative Adversarial Network-Based Magnetic Resonance Image Feature Synthesis for Breast Lesion Classification-Reference-Cited by-同舟云学术

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Cross-Parametric Generative Adversarial Network-Based Magnetic Resonance Image Feature Synthesis for Breast Lesion Classification

Published:2023-11 Issue:11 Volume:27 Page:5495-5505
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Fan Ming¹^ORCID,Huang Guangyao¹^ORCID,Lou Junhong¹^ORCID,Gao Xin²^ORCID,Zeng Tieyong³^ORCID,Li Lihua¹^ORCID

Affiliation:

1. Institute of Institute of Intelligent Biomedicine, Hangzhou Dianzi University, Hangzhou, China

2. Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia

3. Department of Mathematics, The Chinese University of Hong Kong, Hong Kong, SAR, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province of China

King Abdullah University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10311342/10237240.pdf?arnumber=10237240

Reference49 articles.

1. Independent validation of machine learning in diagnosing breast Cancer on magnetic resonance imaging within a single institution

2. Non-Mass Enhancements on DCE-MRI: Development and Validation of a Radiomics-Based Signature for Breast Cancer Diagnoses

3. Breast cancer diagnosis in DCE-MRI using mixture ensemble of convolutional neural networks

4. Deep Convolutional Neural Networks-Based Automatic Breast Segmentation and Mass Detection in DCE-MRI

5. Dynamic contrast-enhanced breast MRI features correlate with invasive breast cancer angiogenesis

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1. Generative adversarial network-based synthesis of contrast-enhanced MR images from precontrast images for predicting histological characteristics in breast cancer;Physics in Medicine & Biology;2024-04-15

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