生物医学中的光声成像
模态(人机交互)
超声成像
计算机科学
光学成像
深度学习
医学影像学
翻译(生物学)
人工智能
光声层析成像
超声波
医学物理学
医学
放射科
光学
迭代重建
化学
物理
基因
信使核糖核酸
生物化学
作者
Praveenbalaji Rajendran,Arunima Sharma,Manojit Pramanik
标识
DOI:10.1007/s13534-021-00210-y
摘要
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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