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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한의용생체공학회 Biomedical Engineering Letters (BMEL) Biomedical Engineering Letters (BMEL) Vol.12 No.2
- 발행연도
- 2022.5
- 수록면
- 155 - 173 (19page)
- DOI
- https://doi.org/10.1007/s13534-021-00210-y
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초록· 키워드
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Photoacoustic imaging (PAI) is an emerging hybrid imaging modality integrating the benefits of both optical and ultrasoundimaging. 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 abilityto improve medical images. Likewise, DL is also widely being used in PAI to overcome some of the limitations of PAI. Inthis review, we provide a comprehensive overview on the various DL techniques employed in PAI along with its promisingadvantages.
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