4.6 Article

Computer-Aided Detection (CADe) System with Optical Coherent Tomography for Melanin Morphology Quantification in Melasma Patients

Journal

DIAGNOSTICS
Volume 11, Issue 8, Pages -

Publisher

MDPI
DOI: 10.3390/diagnostics11081498

Keywords

melasma; melanin; optical coherence tomography; cellular resolution; full-field OCT; photoaging; deep learning; image denoising; convolutional neural networks; computer-aided detection

Funding

  1. CMU Research Fund [109426DC]

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Individuals with dark skin types are more prone to pigmentary disorders, with melasma being particularly difficult to treat and often recurring. Objective measurement of melanin amount is important in evaluating treatment response, with the use of full-field optical coherence tomography and a computer-aided detection system proving to be effective in extracting various melanin features.
Dark skin-type individuals have a greater tendency to have pigmentary disorders, among which melasma is especially refractory to treat and often recurs. Objective measurement of melanin amount helps evaluate the treatment response of pigmentary disorders. However, naked-eye evaluation is subjective to weariness and bias. We used a cellular resolution full-field optical coherence tomography (FF-OCT) to assess melanin features of melasma lesions and perilesional skin on the cheeks of eight Asian patients. A computer-aided detection (CADe) system is proposed to mark and quantify melanin. This system combines spatial compounding-based denoising convolutional neural networks (SC-DnCNN), and through image processing techniques, various types of melanin features, including area, distribution, intensity, and shape, can be extracted. Through evaluations of the image differences between the lesion and perilesional skin, a distribution-based feature of confetti melanin without layering, two distribution-based features of confetti melanin in stratum spinosum, and a distribution-based feature of grain melanin at the dermal-epidermal junction, statistically significant findings were achieved (p-values = 0.0402, 0.0032, 0.0312, and 0.0426, respectively). FF-OCT enables the real-time observation of melanin features, and the CADe system with SC-DnCNN was a precise and objective tool with which to interpret the area, distribution, intensity, and shape of melanin on FF-OCT images.

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