Abstract
Objective-coupled surface plasmon microscopy (SPM) features on both extremely high sensitivity and high resolution. However, this promising system is still operated in laboratories without commercial instrument. One big challenge is how to extract and classify the plasmonic signals from batches of experimentally acquired back focal plane (BFP) images accurately and automatically. To solve this problem, this work presents a complete solution for the first time which significantly promotes the application and instrumentation of BFP-typed SPM in two aspects: 1) it utilizes an object detection model to predetermine the classification and raw localization of plasmonic absorption profiles for the convenience of subsequent fine detection and 2) it utilizes self-correlation to identify the plasmonic signal more accurately; when the mode of plasmonic signal is determined, the self-correlation procedure can operate independently, with faster speed and wider applicability than our previously proposed Fourier correlation analysis. The whole scheme is experimentally verified on our home-developed SPM. And the performance of the proposed scheme is illustrated through comparisons with other approaches.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
