Background/purpose: Hyperpigmentation is a common skin problem that looks darker than normal skin regions. Accurate evaluation of a hyperpigmented lesion (HPL) is of clinical importance because proper choice of treatment can be dependent on it. This study aimed to differentiate between epidermal and dermal HPLs. Methods: Cross-polarized color images (CPCIs) and fluorescence color images (FCIs) were acquired from the same facial regions. Contrast-limited adaptive histogram equalization (CLAHE) was employed to enhance the image contrast and a fuzzy c-means algorithm was implemented to extract the HPLs. The HPLs were superimposed to investigate the difference between CPCI and FCI. Results: The HPL was successfully extracted by applying both CLAHE and fuzzy c-means algorithms. CPCI and FCI resulted in a slightly different HPL, even from the same facial region, indicating a greater percentage area of HPL in FCI than CPCI. Conclusion: CPCI and FCI may be utilized to differentiate HPLs that exist in different skin layers. Thus, this approach may contribute to the effective treatment of HPLs.
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