Deep Unsupervised Learning for Biomedical Image Translation from Harmonic Generation Microscopy Image to H&E-stained Image

Wei Ju Chen; En Yu Liao; Tsung Ming Tai; Yi Hua Liao; Chi Kuang Sun; Cheng Kuang Lee; Simon See; Hung Wen Chen

Deep Unsupervised Learning for Biomedical Image Translation from Harmonic Generation Microscopy Image to H&E-stained Image

Wei Ju Chen, En Yu Liao, Tsung Ming Tai, Yi Hua Liao, Chi Kuang Sun, Cheng Kuang Lee, Simon See, Hung Wen Chen^*

^*Corresponding author for this work

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	2023 Conference on Lasers and Electro-Optics, CLEO 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781957171258
State	Published - 2023
Event	2023 Conference on Lasers and Electro-Optics, CLEO 2023 - San Jose, United States Duration: 07 05 2023 → 12 05 2023

Publication series

Name	2023 Conference on Lasers and Electro-Optics, CLEO 2023

Conference

Conference	2023 Conference on Lasers and Electro-Optics, CLEO 2023
Country/Territory	United States
City	San Jose
Period	07/05/23 → 12/05/23

Bibliographical note

Publisher Copyright:
© 2023 The Author(s)

Keywords

Deep learning
H&E staining
Harmonic generation microscopy (HGM)
Image translation

Cite this

Chen, W. J., Liao, E. Y., Tai, T. M., Liao, Y. H., Sun, C. K., Lee, C. K., See, S., & Chen, H. W. (2023). Deep Unsupervised Learning for Biomedical Image Translation from Harmonic Generation Microscopy Image to H&E-stained Image. In 2023 Conference on Lasers and Electro-Optics, CLEO 2023 Article ATu3Q.6 (2023 Conference on Lasers and Electro-Optics, CLEO 2023). Institute of Electrical and Electronics Engineers Inc..

@inproceedings{2cd3c65d32544ea0af133b87cf523a1e,

title = "Deep Unsupervised Learning for Biomedical Image Translation from Harmonic Generation Microscopy Image to H&E-stained Image",

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.",

keywords = "Deep learning, H&E staining, Harmonic generation microscopy (HGM), Image translation",

author = "Chen, {Wei Ju} and Liao, {En Yu} and Tai, {Tsung Ming} and Liao, {Yi Hua} and Sun, {Chi Kuang} and Lee, {Cheng Kuang} and Simon See and Chen, {Hung Wen}",

note = "Publisher Copyright: {\textcopyright} 2023 The Author(s); 2023 Conference on Lasers and Electro-Optics, CLEO 2023 ; Conference date: 07-05-2023 Through 12-05-2023",

year = "2023",

language = "英语",

series = "2023 Conference on Lasers and Electro-Optics, CLEO 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2023 Conference on Lasers and Electro-Optics, CLEO 2023",

address = "美国",

}

Chen, WJ, Liao, EY, Tai, TM, Liao, YH, Sun, CK, Lee, CK, See, S & Chen, HW 2023, Deep Unsupervised Learning for Biomedical Image Translation from Harmonic Generation Microscopy Image to H&E-stained Image. in 2023 Conference on Lasers and Electro-Optics, CLEO 2023., ATu3Q.6, 2023 Conference on Lasers and Electro-Optics, CLEO 2023, Institute of Electrical and Electronics Engineers Inc., 2023 Conference on Lasers and Electro-Optics, CLEO 2023, San Jose, United States, 07/05/23.

Deep Unsupervised Learning for Biomedical Image Translation from Harmonic Generation Microscopy Image to H&E-stained Image. / Chen, Wei Ju; Liao, En Yu; Tai, Tsung Ming et al.
2023 Conference on Lasers and Electro-Optics, CLEO 2023. Institute of Electrical and Electronics Engineers Inc., 2023. ATu3Q.6 (2023 Conference on Lasers and Electro-Optics, CLEO 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Deep Unsupervised Learning for Biomedical Image Translation from Harmonic Generation Microscopy Image to H&E-stained Image

AU - Chen, Wei Ju

AU - Liao, En Yu

AU - Tai, Tsung Ming

AU - Liao, Yi Hua

AU - Sun, Chi Kuang

AU - Lee, Cheng Kuang

AU - See, Simon

AU - Chen, Hung Wen

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

KW - Deep learning

KW - H&E staining

KW - Harmonic generation microscopy (HGM)

KW - Image translation

UR - http://www.scopus.com/inward/record.url?scp=85176311704&partnerID=8YFLogxK

M3 - 会议稿件

AN - SCOPUS:85176311704

T3 - 2023 Conference on Lasers and Electro-Optics, CLEO 2023

BT - 2023 Conference on Lasers and Electro-Optics, CLEO 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 Conference on Lasers and Electro-Optics, CLEO 2023

Y2 - 7 May 2023 through 12 May 2023

ER -

Deep Unsupervised Learning for Biomedical Image Translation from Harmonic Generation Microscopy Image to H&E-stained Image

Abstract

Publication series

Conference

Bibliographical note

Keywords

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Cite this