Photoacoustic imaging aided with deep learning: a review
Photoacoustic imaging (PAI) is an emerging hybrid imaging modality integrating the benefits of both optical and ultrasound imaging. Although PAI exhibits superior imaging capabilities, its translation into clinics is still hindered by various limitations. In recent years, deeplearning (DL), a new pa...
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sg-ntu-dr.10356-1571172023-12-29T06:49:53Z Photoacoustic imaging aided with deep learning: a review Rajendran, Praveenbalaji Sharma, Arunima Pramanik, Manojit School of Chemical and Biomedical Engineering Engineering::Bioengineering Photoacoustic Tomography Photoacoustic Microscopy Photoacoustic imaging (PAI) is an emerging hybrid imaging modality integrating the benefits of both optical and ultrasound imaging. Although PAI exhibits superior imaging capabilities, its translation into clinics is still hindered by various limitations. In recent years, deeplearning (DL), a new paradigm of machine learning, is gaining a lot of attention due to its ability to improve medical images. Likewise, DL is also widely being used in PAI to overcome some of the limitations of PAI. In this review, we provide a comprehensive overview on the various DL techniques employed in PAI along with its promising advantages. Ministry of Education (MOE) Submitted/Accepted version The author would like to acknowledge the support by Tier 1 Grant funded by the Ministry of Education in Singapore (RG144/18, RG127/19). 2022-05-09T01:15:43Z 2022-05-09T01:15:43Z 2022 Journal Article Rajendran, P., Sharma, A. & Pramanik, M. (2022). Photoacoustic imaging aided with deep learning: a review. Biomedical Engineering Letters, 12(2), 155-173. https://dx.doi.org/10.1007/s13534-021-00210-y 2093-9868 https://hdl.handle.net/10356/157117 10.1007/s13534-021-00210-y 2-s2.0-85119887653 2 12 155 173 en RG144/18 RG127/19 Biomedical Engineering Letters © 2021 Korean Society of Medical and Biological Engineering. All rights reserved. This paper was published in Biomedical Engineering Letters and is made available with permission of Korean Society of Medical and Biological Engineering. application/pdf |
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Engineering::Bioengineering Photoacoustic Tomography Photoacoustic Microscopy Rajendran, Praveenbalaji Sharma, Arunima Pramanik, Manojit Photoacoustic imaging aided with deep learning: a review |
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Photoacoustic imaging (PAI) is an emerging hybrid imaging modality integrating the benefits of both optical and ultrasound imaging. Although PAI exhibits superior imaging capabilities, its translation into clinics is still hindered by various limitations. In recent years, deeplearning (DL), a new paradigm of machine learning, is gaining a lot of attention due to its ability to improve medical images. Likewise, DL is also widely being used in PAI to overcome some of the limitations of PAI. In this review, we provide a comprehensive overview on the various DL techniques employed in PAI along with its promising advantages. |
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School of Chemical and Biomedical Engineering |
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School of Chemical and Biomedical Engineering Rajendran, Praveenbalaji Sharma, Arunima Pramanik, Manojit |
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Article |
author |
Rajendran, Praveenbalaji Sharma, Arunima Pramanik, Manojit |
author_sort |
Rajendran, Praveenbalaji |
title |
Photoacoustic imaging aided with deep learning: a review |
title_short |
Photoacoustic imaging aided with deep learning: a review |
title_full |
Photoacoustic imaging aided with deep learning: a review |
title_fullStr |
Photoacoustic imaging aided with deep learning: a review |
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Photoacoustic imaging aided with deep learning: a review |
title_sort |
photoacoustic imaging aided with deep learning: a review |
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2022 |
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https://hdl.handle.net/10356/157117 |
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1787136646389432320 |