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Improving needle visibility in LED-based photoacoustic imaging using deep learning with semi-synthetic datasets.

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第一作者： Mengjie,Shi

第一单位： School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, United Kingdom.

作者： Mengjie,Shi ^[1] ; Tianrui,Zhao ^[1] ; Simeon J,West ^[2] ; Adrien E,Desjardins ^[3] ; Tom,Vercauteren ^[1] ; Wenfeng,Xia ^[1]

作者单位： School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, United Kingdom. ^[1] Department of Anaesthesia, University College Hospital, London NW1 2BU, United Kingdom. ^[2] Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London W1 W 7TY, United Kingdom.;Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, United Kingdom. ^[3]

关键词 Deep learning Light emitting diodes Minimally invasive procedures Needle visibility Photoacoustic imaging

DOI 10.1016/j.pacs.2022.100351

PMID 35495095

发布时间 2022-07-16

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Improving needle visibility in LED-based photoacoustic imaging using deep learning with semi-synthetic datasets.

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Improving needle visibility in LED-based photoacoustic imaging using deep learning with semi-synthetic datasets.

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