Abstract

Diagnosis of many skin conditions requires evaluation of dermal papillae and stratum basale, such as vitiligo. In clinical practice, imaging dermal papillae structures relies on excisional biopsy followed by histological processing and analysis. As biopsy is invasive and associated with complications, a noninvasive imaging method such as optical coherence tomography (OCT) can complement the existing method by enabling large area scanning. However, because OCT image analysis requires training and it takes time to review OCT images from large skin areas, an automatic evaluation method is preferred to reduce the workload and avoid ‘sampling errors’ during image analysis. Here we report an automatic method to enhance and detect dermal papillae and stratum basale in ultrahigh resolution OCT images. A high detection accuracy is achieved by rejecting image artifacts using a surface flattening algorithm and an artifact recognition algorithm. We further demonstrated the efficacy of this automatic method in detecting vitiligo in human subjects.

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