Boundary-Preserved Deep Denoising of Stochastic Resonance Enhanced Multiphoton Images-Reference-Cited by-同舟云学术

Boundary-Preserved Deep Denoising of Stochastic Resonance Enhanced Multiphoton Images

Published:2022 Issue: Volume:10 Page:1-12
ISSN:2168-2372
Container-title:IEEE Journal of Translational Engineering in Health and Medicine
language:
Short-container-title:IEEE J. Transl. Eng. Health Med.

Author:

Niu Sheng-Yong¹,Guo Lun-Zhang²,Li Yue³,Zhang Zhiming³,Wang Tzung-Dau⁴^ORCID,Liu Kai-Chun¹^ORCID,Li You-Jin¹,Tsao Yu¹^ORCID,Liu Tzu-Ming³

Affiliation:

1. Research Center for Information Technology Innovation (CITI), Academia Sinica, Taipei, Taiwan

2. Department of Biomedical Engineering, National Taiwan University, Taipei, Taiwan

3. Institute of Translational Medicine, Faculty of Health Sciences & Ministry of Education Frontiers Science Center for Precision Oncology, University of Macau, Taipa, Macau, China

4. Department of Internal Medicine, Cardiovascular Center and Division of Cardiology, College of Medicine, National Taiwan University Hospital, Taipei, Taiwan

Funder

Faculty of Health Sciences, University of Macau, the startup Grants of the University of Macau

Science and Technology Development Fund, Macau SAR

Cardiovascular Center, Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, Ministry of Science and Technology, R.O.C

Academia Sinica

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Medicine

Link

http://xplorestaging.ieee.org/ielx7/6221039/9652399/09889701.pdf?arnumber=9889701

Reference44 articles.

1. A Poisson-Gaussian Denoising Dataset With Real Fluorescence Microscopy Images

2. Image Quality Assessment: From Error Visibility to Structural Similarity

3. Content-aware image restoration: pushing the limits of fluorescence microscopy

4. Image Processing

5. U-Net: Convolutional Networks for Biomedical Image Segmentation

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