Integration of cellular-resolution optical coherence tomography and Raman spectroscopy for discrimination of skin cancer cells with machine learning.

ABSTRACT:

Significance

An integrated cellular-resolution optical coherence tomography (OCT) module with near-infrared Raman spectroscopy was developed on the discrimination of various skin cancer cells and normal cells. Micron-level three-dimensional (3D) spatial resolution and the spectroscopic capability on chemical component determination can be obtained simultaneously.

Aim

We experimentally verified the effectiveness of morphology, intensity, and spectroscopy features for discriminating skin cells.

Approach

Both spatial and spectroscopic features were employed for the discrimination of five types of skin cells, including keratinocytes (HaCaT), the cell line of squamous cell carcinoma (A431), the cell line of basal cell carcinoma (BCC-1/KMC), primary melanocytes, and the cel

SUBMITTER: You C 

PROVIDER: S-EPMC10500347 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature