Lung cancer is difficult to detect using Raman spectroscopy, particularly due to tar fluorescence. We demonstrate improved performance for Raman classifiers by using fixed tissue sections and compare results with immunohistochemistry and hematoxylin and eosin (H&E) staining. In addition to eliminating fluorescence, fixed samples provide the flexibility of additional measurements and provide greater detail in borderline cases. Reliable classifiers based on Raman features would provide an additional tool to detect lung cancer during medical procedures would benefit patients and save medical resources.
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