Automated Baseline Correction Evaluation Score for Raman Spectroscopy

Area of Science:

• Biomedical Optics
• Spectroscopy
• Data Analysis

Background:

• Raman spectroscopy offers molecular insights for diagnostics but requires accurate baseline correction.
• Current visual assessment of baseline correction is subjective and time-consuming.
• Automated methods are needed for large-scale clinical Raman data analysis.

Purpose of the Study:

• To introduce the Integrity Spectrum (IS) Score, a novel quantitative metric for evaluating Raman spectral baseline correction.
• To provide an automated and objective alternative to manual visual inspection.

Main Methods:

• The IS Score algorithm analyzes spectral properties like band prominence, area-under-the-curve differences, and baseline deviations.
• It quantifies underfitting and overfitting without needing ground truth data.
• The method was validated on complex two-layered blood cell Raman spectra.

Main Results:

• The IS Score demonstrated a strong correlation with expert visual evaluations of baseline correction quality.
• Automated scoring significantly reduced the time required for assessment.
• The method effectively identified both underfitting and overfitting issues.

Conclusions:

• The IS Score offers a reliable, objective, and efficient solution for assessing Raman spectroscopy baseline correction.
• This facilitates consistent data processing in multicenter studies, reducing bias and enhancing comparability.
• The IS Score improves the overall reliability of Raman spectroscopy for clinical applications.