Automatic Detection of Blue-White Veil and Related Structures in Dermoscopy Images

09/06/2010 ∙ by M. Emre Celebi, et al. ∙ 0 ∙ share

Dermoscopy is a non-invasive skin imaging technique, which permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. One of the most important features for the diagnosis of melanoma in dermoscopy images is the blue-white veil (irregular, structureless areas of confluent blue pigmentation with an overlying white "ground-glass" film). In this article, we present a machine learning approach to the detection of blue-white veil and related structures in dermoscopy images. The method involves contextual pixel classification using a decision tree classifier. The percentage of blue-white areas detected in a lesion combined with a simple shape descriptor yielded a sensitivity of 69.35 and a specificity of 89.97 rises to 78.20 feature for melanoma recognition.

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Automatic Detection of Blue-White Veil and Related Structures in Dermoscopy Images

Authors

Disease Classification within Dermascopic Images Using features extracted by ResNet50 and classification through Deep Forest

White Paper Assistance: A Step Forward Beyond the Shortcut Learning

Segmentation and Classification of Skin Lesions for Disease Diagnosis

Automatic Skin Lesion Analysis using Large-scale Dermoscopy Images and Deep Residual Networks

High Accuracy Classification of White Blood Cells using TSLDA Classifier and Covariance Features

The Cyborg Astrobiologist: Scouting Red Beds for Uncommon Features with Geological Significance

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