Optimized spectral filter design enables more accurate estimation of oxygen saturation in spectral imaging.

ABSTRACT: Oxygen saturation (SO₂) in tissue is a crucially important physiological parameter with ubiquitous clinical utility in diagnosis, treatment, and monitoring, as well as widespread use as an invaluable preclinical research tool. Multispectral imaging can be used to visualize SO₂ non-invasively, non-destructively and without contact in real-time using narrow spectral filter sets, but typically, these spectral filter sets are poorly suited to a specific clinical task, application, or tissue type. In this work, we demonstrate the merit of optimizing spectral filter sets for more accurate estimation of SO₂. Using tissue modelling and simulated multispectral imaging, we demonstrate filter optimization reduces the root-mean-square-error (RMSE) in estimating SO

SUBMITTER: J Waterhouse D 

PROVIDER: S-EPMC9045927 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature