Multi-Label Local to Global Learning: A Novel Learning Paradigm for Chest X-Ray Abnormality Classification-Reference-Cited by-同舟云学术

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Multi-Label Local to Global Learning: A Novel Learning Paradigm for Chest X-Ray Abnormality Classification

Published:2023-09 Issue:9 Volume:27 Page:4409-4420
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Liu Zean¹,Cheng Yuanzhi²^ORCID,Tamura Shinichi³^ORCID

Affiliation:

1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China

2. School of Information Science and Technology, Qingdao University of Science and Technology, Qingdao, China

3. Department of Radiology, Graduate School of Medicine, Osaka University, Osaka, Japan

Funder

Grants-in-Aid for Scientific Research of Exploratory Research

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/ielx7/6221020/10242175/10138546.pdf?arnumber=10138546

Reference53 articles.

1. TieNet: Text-Image Embedding Network for Common Thorax Disease Classification and Reporting in Chest X-Rays

2. Triple attention learning for classification of 14 thoracic diseases using chest radiography

3. ImageGCN: Multi-Relational Image Graph Convolutional Networks for Disease Identification With Chest X-Rays

4. Indication as Prior Knowledge for Multimodal Disease Classification in Chest Radiographs with Transformers

5. Towards evaluating the robustness of deep diagnostic models by adversarial attack

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. Investigating the impact of novel XRayGAN in feature extraction for thoracic disease detection in chest radiographs: lung cancer;Signal, Image and Video Processing;2024-05-08

2. Chest x-ray diagnosis via spatial-channel high-order attention representation learning;Physics in Medicine & Biology;2024-02-13

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