AI-assisted identification of nonmelanoma skin cancer structures based on combined line-field confocal optical coherence tomography and confocal Raman microspectroscopy.

ABSTRACT:

Significance

Morpho-chemical characterization of skin cancers provides valuable insights for early diagnosis, classification, and treatment response assessment.

Aim

We introduce a compact, noninvasive system combining high-resolution morphological imaging and chemical characterization of skin tissues. The system integrates line-field confocal optical coherence tomography for cellular-level imaging and confocal Raman microspectroscopy to analyze the chemical composition of specific targets identified within the morphological images.

Approach

We present results obtained from the system installed in a clinical setting over the course of 1 year. More than 330 nonmelanoma skin cancer specimens were imaged ex vivo, with different structures targeted for Raman microsp

SUBMITTER: Ayadh M 

PROVIDER: S-EPMC12302994 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature