Artificially Generated Visual Scanpath Improves Multilabel Thoracic Disease Classification in Chest X-Ray Images-Reference-Cited by-同舟云学术

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Artificially Generated Visual Scanpath Improves Multilabel Thoracic Disease Classification in Chest X-Ray Images

Published:2024 Issue: Volume:73 Page:1-11
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Verma Ashish¹^ORCID,Kar Aupendu¹^ORCID,Ghosh Krishnendu¹^ORCID,Dhara Sobhan Kanti²^ORCID,Sen Debashis¹^ORCID,Kumar Biswas Prabir¹^ORCID

Affiliation:

1. Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology at Kharagpur, Kharagpur, India

2. Department of Electronics and Communication Engineering, National Institute of Technology at Rourkela, Rourkela, India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/19/10367905/10599335.pdf?arnumber=10599335

Reference70 articles.

1. Deep learning for chest X-ray analysis: A survey

2. Noninvasive COVID-19 Screening Using Deep-Learning-Based Multilevel Fusion Model With an Attention Mechanism

3. 3DSRNet: 3-D Spine Reconstruction Network Using 2-D Orthogonal X-Ray Images Based on Deep Learning

4. Classify and Localize Threat Items in X-Ray Imagery With Multiple Attention Mechanism and High-Resolution and High-Semantic Features

5. Interpretation of Plain Chest Roentgenogram

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