Validation of spectral imaging database generation for skin diagnosis through monte carlo simulation - real measurement comparison

Spectral imaging has recently gained attention as a promising noninvasive technique for diagnosing human skin conditions, owing to its safety and noninvasive nature. However, one of the main challenges to advancing the application of this technique is the lack of a comprehensive and reliable database capturing the optical characteristics of different skin tones and conditions. Monte Carlo Simulation on Multi-layer Media (MCML) has proven effective in modeling light-tissue interactions and generating spectral reflectance data for biological tissues, particularly skin. However, the traditional simulation process is time-consuming. This study examines and validates the results of an accelerated MCML simulation using CUDA technology, by comparing its spectral diffuse reflectance outputs with actual measurements from healthy skin across three distinct skin tones within the 900 nm to 1700 nm wavelength range. The high degree of agreement between simulated and measured data supports the feasibility of building a robust MCML-based spectral reflectance database.