Deep Unsupervised Learning for Biomedical Image Translation from Harmonic Generation Microscopy Image to H&E-stained Image
2023 Conference on Lasers and Electro-Optics (CLEO)（2023）
Abstract
This work proposes an unsupervised deep learning-based image translation from Harmonic generation microscopy (HGM) to widely used H&E-stained images. The proposed methodology is promising and hopefully will facilitate adopting HGM in clinical workflows.
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Key words
Harmonic generation microscopy (HGM),H&E staining,Deep learning,Image translation
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