Dale J. Waterhouse,1 Laura Privitera,2,1 Danail Stoyanov,1 Stefano Giuliani3
1EPSRC Ctr. for Interventional and Surgical Sciences, Univ. College London (United Kingdom) 2UCL Great Ormond Street Institute of Child Health (United Kingdom) 3Great Ormond St Hospital for Children NHS Foundation Trust (United Kingdom)
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
Fluorescence-guided surgery (FGS) provides real-time visualisation of tumours with molecular specificity, but intensity-based measurement of fluorescence is prone to errors. Multispectral imaging (MSI) in the short-wave infrared (SWIR) has the potential to improve tumour delineation by enabling machine-learning-based classification of pixels based on their spectral characteristics. In this work, we demonstrate the ability of this approach to provide a robust method of visualizing tumour tissue during FGS.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.