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Conference 11960 > Paper 11960-53
Paper 11960-53

AI-enabled high-speed photoacoustic endomicroscopy through a multimode fibre

Abstract

Photoacoustic (PA) endoscopy has attracted intense research interest recently for the guidance of minimally invasive procedures. In this work, we developed a video-rate ultrathin endo-microscopy imaging system based on a multimode fibre. A deep image prior (DIP) neural network was used to improve the imaging speed and spatial resolution using unsupervised learning. High-fidelity PA images of carbon fibre phantoms and mouse blood cells were acquired at video-rate. We anticipate that with further minimisation of the ultrasound detector, this imaging system could be applied for the guidance of interventional and surgical operations such as fetal surgery and tumour surgery.

Presenter

Tianrui Zhao
King's College London (United Kingdom)
Tianrui Zhao is a PhD student in the School of Biomedical Engineering & Imaging Sciences at King’s College London, UK. He received his B.Sc. in Materials Science and Engineering from Northwestern Polytechnical University, China, and M.Sc. degree in Materials for Energy and Environment from University College London, UK, in 2015 and 2016, respectively. His research interests include developing minimally invasive imaging devices based on photoacoustic imaging.
Presenter/Author
Tianrui Zhao
King's College London (United Kingdom)
Author
King's College London (United Kingdom)
Author
King's College London (United Kingdom)
Author
King's College London (United Kingdom)
Author
King's College London (United Kingdom)