The present disclosure provides for a system and method for diagnosing biological samples that combines the visual staining features familiar to pathologists with the accurate, reliable, and nondestructive capabilities of Raman chemical imaging. The invention disclosed herein may be applied to diagnose lung cancer samples. A method may comprise illuminating a biological sample to generate interacted photons, filtering said interacted photons using a tunable filter, and detecting interacted photons to generate a test Raman data set representative of said sample. The method may further comprise applying at least one chemometric technique and/or a digital stain to said test Raman data set. This test Raman data set may be analyzed to diagnose said sample as comprising at least one of: adenocarcinoma, mesothelioma, and combinations thereof. A system may comprise an illumination source, a tunable filter, and a detector configured to generate a test Raman data set representative of a biological sample.
