On-the-fly Raman microscopy guaranteeing the accuracy of discrimination.

ABSTRACT: Accelerating the measurement for discrimination of samples, such as classification of cell phenotype, is crucial when faced with significant time and cost constraints. Spontaneous Raman microscopy offers label-free, rich chemical information but suffers from long acquisition time due to extremely small scattering cross-sections. One possible approach to accelerate the measurement is by measuring necessary parts with a suitable number of illumination points. However, how to design these points during measurement remains a challenge. To address this, we developed an imaging technique based on a reinforcement learning in machine learning (ML). This ML approach adaptively feeds back "optimal" illumination pattern during the measurement to detect the existence of specific characteristics of int

SUBMITTER: Tabata K 

PROVIDER: S-EPMC10962959 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature