CycleGAN with mutual information loss constraint generates structurally aligned CT images from functional EIT images
Author:
Affiliation:
1. Gense Technologies Ltd.,Hong Kong,China
2. The University of Hong Kong,Li Ka Shing Faculty of Medicine,Department of Diagnostic Radiology,Hong Kong,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10339936/10339939/10340711.pdf?arnumber=10340711
Reference20 articles.
1. A review of electrical impedance tomography in lung applications: Theory and algorithms for absolute images
2. Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks
3. Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method
4. Affordable, portable and self-administrable electrical impedance tomography enables global and regional lung function assessment
5. Standalone electrical impedance tomography predicts spirometry indicators and enables regional lung assessment
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1. GAN Synergy: Transfer Learning-based Annotated Left Atrium MR Imaging Generation with Paired and Unpaired Models;2024 International Seminar on Intelligent Technology and Its Applications (ISITIA);2024-07-10
2. Enhanced Synthetic MRI Generation from CT Scans Using CycleGAN with Feature Extraction;2023 Seventh International Conference on Image Information Processing (ICIIP);2023-11-22
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