High frame rate (∼3 Hz) circular photoacoustic tomography using single-element ultrasound transducer aided with deep learning
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 usi...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2022
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| Online Access: | https://hdl.handle.net/10356/161291 |
| _version_ | 1826114706950062080 |
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| author | Rajendran, Praveenbalaji Pramanik, Manojit |
| author2 | School of Chemical and Biomedical Engineering |
| author_facet | School of Chemical and Biomedical Engineering Rajendran, Praveenbalaji Pramanik, Manojit |
| author_sort | Rajendran, Praveenbalaji |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T03:43:31Z |
| format | Journal Article |
| id | ntu-10356/161291 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:43:31Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1612912023-12-29T06:46:54Z High frame rate (∼3 Hz) circular photoacoustic tomography using single-element ultrasound transducer aided with deep learning Rajendran, Praveenbalaji Pramanik, Manojit School of Chemical and Biomedical Engineering Engineering::Bioengineering Photoacoustic Tomography High Framerate Imaging 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. Ministry of Education (MOE) Published version The author would like to acknowledge the support by the Tier 1 Grant funded by the Ministry of Education in Singapore (RG30/21). 2022-08-24T02:06:47Z 2022-08-24T02:06:47Z 2022 Journal Article 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 1083-3668 https://hdl.handle.net/10356/161291 10.1117/1.JBO.27.6.066005 2-s2.0-85133705171 6 27 066005-1 066005-14 en RG30/21 Journal of Biomedical Optics © 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] application/pdf |
| spellingShingle | Engineering::Bioengineering Photoacoustic Tomography High Framerate Imaging Rajendran, Praveenbalaji Pramanik, Manojit High frame rate (∼3 Hz) circular photoacoustic tomography using single-element ultrasound transducer aided with deep learning |
| title | High frame rate (∼3 Hz) circular photoacoustic tomography using single-element ultrasound transducer aided with deep learning |
| title_full | High frame rate (∼3 Hz) circular photoacoustic tomography using single-element ultrasound transducer aided with deep learning |
| title_fullStr | High frame rate (∼3 Hz) circular photoacoustic tomography using single-element ultrasound transducer aided with deep learning |
| title_full_unstemmed | High frame rate (∼3 Hz) circular photoacoustic tomography using single-element ultrasound transducer aided with deep learning |
| title_short | High frame rate (∼3 Hz) circular photoacoustic tomography using single-element ultrasound transducer aided with deep learning |
| title_sort | high frame rate ∼3 hz circular photoacoustic tomography using single element ultrasound transducer aided with deep learning |
| topic | Engineering::Bioengineering Photoacoustic Tomography High Framerate Imaging |
| url | https://hdl.handle.net/10356/161291 |
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