De-Noising of Photoacoustic Microscopy Images by Attentive Generative Adversarial Network-Reference-Cited by-同舟云学术

De-Noising of Photoacoustic Microscopy Images by Attentive Generative Adversarial Network

Published:2023-05 Issue:5 Volume:42 Page:1349-1362
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

He Da¹^ORCID,Zhou Jiasheng²^ORCID,Shang Xiaoyu¹,Tang Xingye¹,Luo Jiajia³^ORCID,Chen Sung-Liang¹^ORCID

Affiliation:

1. University of Michigan-Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, China

2. University of Michigan-Shanghai Jiao Tong University Joint Institute, and the Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China

3. Institute of Medical Technology, Peking University Health Science Center, Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Natural Science Foundation of Shanghai, China

Peking University Clinical Medicine Plus X-Young Scholars Project

PKU-Baidu Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software

Link

http://xplorestaging.ieee.org/ielx7/42/10114431/09970755.pdf?arnumber=9970755

Reference52 articles.

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4. De‐noising of photoacoustic sensing and imaging based on combined empirical mode decomposition and independent component analysis

5. Super Wide-Field Photoacoustic Microscopy of Animals and Humans In Vivo

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