Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/161291
Title: High frame rate (∼3 Hz) circular photoacoustic tomography using single-element ultrasound transducer aided with deep learning
Authors: Rajendran, Praveenbalaji
Pramanik, Manojit
Keywords: Engineering::Bioengineering
Issue Date: 2022
Source: Rajendran, P. & Pramanik, M. (2022). High frame rate (∼3 Hz) circular photoacoustic tomography using single-element ultrasound transducer aided with deep learning. Journal of Biomedical Optics, 27(6), 066005-1-066005-14. https://dx.doi.org/10.1117/1.JBO.27.6.066005
Project: RG30/21 
Journal: Journal of Biomedical Optics 
Abstract: Significance: In circular scanning photoacoustic tomography (PAT), it takes several minutes to generate an image of acceptable quality, especially with a single-element ultrasound transducer (UST). The imaging speed can be enhanced by faster scanning (with high repetition rate light sources) and using multiple-USTs. However, artifacts arising from the sparse signal acquisition and low signal-to-noise ratio at higher scanning speeds limit the imaging speed. Thus, there is a need to improve the imaging speed of the PAT systems without hampering the quality of the PAT image. Aim: To improve the frame rate (or imaging speed) of the PAT system by using deep learning (DL). Approach: For improving the frame rate (or imaging speed) of the PAT system, we propose a novel U-Net-based DL framework to reconstruct PAT images from fast scanning data. Results: The efficiency of the network was evaluated on both single-and multiple-UST-based PAT systems. Both phantom and in vivo imaging demonstrate that the network can improve the imaging frame rate by approximately sixfold in single-UST-based PAT systems and by approximately twofold in multi-UST-based PAT systems. Conclusions: We proposed an innovative method to improve the frame rate (or imaging speed) by using DL and with this method, the fastest frame rate of ∼3 Hz imaging is achieved without hampering the quality of the reconstructed image.
URI: https://hdl.handle.net/10356/161291
ISSN: 1083-3668
DOI: 10.1117/1.JBO.27.6.066005
Schools: School of Chemical and Biomedical Engineering 
Rights: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. [DOI: 10.1117/1.JBO.27.6.066005]
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCBE Journal Articles

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