Detection of Atypical Texture Features in Early Malignant Melanoma


Background: The presence of an atypical (irregular) pigment network (APN) can indicate a diagnosis of melanoma. This study sought to analyze the APN with texture measures. Methods: For 106 dermoscopy images including 28 melanomas and 78 benign dysplastic nevi, the areas of APN were selected manually. Ten texture measures in the CVIPtools image analysis system were applied. Results: Of the 10 texture measures used, correlation average provided the highest discrimination accuracy, an average of 95.4%. Discrimination of melanomas was optimal at a pixel distance of 20 for the 768 x 512 images, consistent with a melanocytic lesion texel size estimate of 4-5 texels per mm. Conclusion: Texture analysis, in particular correlation average at an optimized pixel spacing, may afford automatic detection of an irregular pigment network in early malignant melanoma.


Electrical and Computer Engineering

Second Department


Keywords and Phrases

Automatic Detection; Dermoscopy; Dermoscopy Images; Discrimination Accuracy; Dysplastic Nevi; Image Analysis Systems; Malignant Melanoma; Melanocytic Lesion; Pixel Spacing; Texture Analysis; Texture Features; Dermatology; Diagnosis; Image Analysis; Oncology; Pixels; Textures; Clinical Feature; Controlled Study; Cutaneous Parameters; Dysplastic Nevus; Epiluminescence Microscopy; Human; Image Analysis; Image Display; Major Clinical Study; Melanoma; Skin Examination; Skin Pigmentation; Tumor Classification; Carcinoma in Situ; Databases; Factual; Dermoscopy; Diagnosis; Differential; Dysplastic Nevus Syndrome; Early Diagnosis; Humans; Hutchinson's Melanotic Freckle; Image Processing; Computer-assisted; Melanoma; Reproducibility of Results; Skin Neoplasms

International Standard Serial Number (ISSN)


Document Type

Article - Journal

Document Version


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© 2010 Wiley-Blackwell, All rights reserved.

Publication Date

01 Feb 2010