Autoencoder based blind source separation for photoacoustic resolution enhancement

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...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Matan Benyamin, Hadar Genish, Ran Califa, Lauren Wolbromsky, Michal Ganani, Zhen Wang, Shuyun Zhou, Zheng Xie, Zeev Zalevsky
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/9d9edd296157414cbb538a316af4d746
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:9d9edd296157414cbb538a316af4d746
record_format	dspace
spelling	oai:doaj.org-article:9d9edd296157414cbb538a316af4d7462021-12-02T12:33:14ZAutoencoder based blind source separation for photoacoustic resolution enhancement10.1038/s41598-020-78310-52045-2322https://doaj.org/article/9d9edd296157414cbb538a316af4d7462020-12-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-78310-5https://doaj.org/toc/2045-2322Abstract 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.Matan BenyaminHadar GenishRan CalifaLauren WolbromskyMichal GananiZhen WangShuyun ZhouZheng XieZeev ZalevskyNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-7 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Matan Benyamin Hadar Genish Ran Califa Lauren Wolbromsky Michal Ganani Zhen Wang Shuyun Zhou Zheng Xie Zeev Zalevsky Autoencoder based blind source separation for photoacoustic resolution enhancement
description	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.
format	article
author	Matan Benyamin Hadar Genish Ran Califa Lauren Wolbromsky Michal Ganani Zhen Wang Shuyun Zhou Zheng Xie Zeev Zalevsky
author_facet	Matan Benyamin Hadar Genish Ran Califa Lauren Wolbromsky Michal Ganani Zhen Wang Shuyun Zhou Zheng Xie Zeev Zalevsky
author_sort	Matan Benyamin
title	Autoencoder based blind source separation for photoacoustic resolution enhancement
title_short	Autoencoder based blind source separation for photoacoustic resolution enhancement
title_full	Autoencoder based blind source separation for photoacoustic resolution enhancement
title_fullStr	Autoencoder based blind source separation for photoacoustic resolution enhancement
title_full_unstemmed	Autoencoder based blind source separation for photoacoustic resolution enhancement
title_sort	autoencoder based blind source separation for photoacoustic resolution enhancement
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/9d9edd296157414cbb538a316af4d746
work_keys_str_mv	AT matanbenyamin autoencoderbasedblindsourceseparationforphotoacousticresolutionenhancement AT hadargenish autoencoderbasedblindsourceseparationforphotoacousticresolutionenhancement AT rancalifa autoencoderbasedblindsourceseparationforphotoacousticresolutionenhancement AT laurenwolbromsky autoencoderbasedblindsourceseparationforphotoacousticresolutionenhancement AT michalganani autoencoderbasedblindsourceseparationforphotoacousticresolutionenhancement AT zhenwang autoencoderbasedblindsourceseparationforphotoacousticresolutionenhancement AT shuyunzhou autoencoderbasedblindsourceseparationforphotoacousticresolutionenhancement AT zhengxie autoencoderbasedblindsourceseparationforphotoacousticresolutionenhancement AT zeevzalevsky autoencoderbasedblindsourceseparationforphotoacousticresolutionenhancement
_version_	1718393876009451520

Autoencoder based blind source separation for photoacoustic resolution enhancement

Ejemplares similares