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Autoencoder based blind source separation for photoacoustic resolution enhancement.

Authors :
Benyamin, Matan
Genish, Hadar
Califa, Ran
Wolbromsky, Lauren
Ganani, Michal
Wang, Zhen
Zhou, Shuyun
Xie, Zheng
Zalevsky, Zeev
Source :
Scientific Reports. 12/8/2020, Vol. 10 Issue 1, p1-7. 7p.
Publication Year :
2020

Abstract

Photoacoustics is a promising technique for in-depth imaging of biological tissues. However, the lateral resolution of photoacoustic imaging is limited by size of the optical excitation spot, and therefore by light diffraction and scattering. Several super-resolution approaches, among which methods based on localization of labels and particles, have been suggested, presenting promising but limited solutions. This work demonstrates a novel concept for extended-resolution imaging based on separation and localization of multiple sub-pixel absorbers, each characterized by a distinct acoustic response. Sparse autoencoder algorithm is used to blindly decompose the acoustic signal into its various sources and resolve sub-pixel features. This method can be used independently or as a combination with other super-resolution techniques to gain further resolution enhancement and may also be extended to other imaging schemes. In this paper, the general idea is presented in details and experimentally demonstrated. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20452322
Volume :
10
Issue :
1
Database :
Academic Search Index
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
147479716
Full Text :
https://doi.org/10.1038/s41598-020-78310-5