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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Bibliographic Details
Main Authors: Rajendran, Praveenbalaji, Sharma, Arunima, Pramanik, Manojit
Other Authors: School of Chemical and Biomedical Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/157117
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Institution: Nanyang Technological University
Language: English
Description
Summary: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.