Open Access
1 March 2011 Pilot study of semiautomated localization of the dermal/epidermal junction in reflectance confocal microscopy images of skin
Sila Kurugol, Jennifer G. Dy, Dana H. Brooks, Milind Rajadhyaksha
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Abstract
Reflectance confocal microscopy (RCM) continues to be translated toward the detection of skin cancers in vivo. Automated image analysis may help clinicians and accelerate clinical acceptance of RCM. For screening and diagnosis of cancer, the dermal/epidermal junction (DEJ), at which melanomas and basal cell carcinomas originate, is an important feature in skin. In RCM images, the DEJ is marked by optically subtle changes and features and is difficult to detect purely by visual examination. Challenges for automation of DEJ detection include heterogeneity of skin tissue, high inter-, intra-subject variability, and low optical contrast. To cope with these challenges, we propose a semiautomated hybrid sequence segmentation/classification algorithm that partitions z-stacks of tiles into homogeneous segments by fitting a model of skin layer dynamics and then classifies tile segments as epidermis, dermis, or transitional DEJ region using texture features. We evaluate two different training scenarios: 1. training and testing on portions of the same stack; 2. training on one labeled stack and testing on one from a different subject with similar skin type. Initial results demonstrate the detectability of the DEJ in both scenarios with epidermis/dermis misclassification rates smaller than 10% and average distance from the expert labeled boundaries around 8.5 μm.
©(2011) Society of Photo-Optical Instrumentation Engineers (SPIE)
Sila Kurugol, Jennifer G. Dy, Dana H. Brooks, and Milind Rajadhyaksha "Pilot study of semiautomated localization of the dermal/epidermal junction in reflectance confocal microscopy images of skin," Journal of Biomedical Optics 16(3), 036005 (1 March 2011). https://doi.org/10.1117/1.3549740
Published: 1 March 2011
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CITATIONS
Cited by 30 scholarly publications and 1 patent.
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KEYWORDS
Skin

Image segmentation

Confocal microscopy

Reflectivity

Matrices

In vivo imaging

Skin cancer

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