Detection of blue-white veil areas in dermoscopy images using machine learning techniques

M. Emre Celebi; Hassan A. Kingravi; Y. Alp Aslandogan; William V. Stoecker

doi:10.1117/12.655779

17 March 2006 Detection of blue-white veil areas in dermoscopy images using machine learning techniques

M. Emre Celebi, Hassan A. Kingravi, Y. Alp Aslandogan, William V. Stoecker

Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 61445T (2006) https://doi.org/10.1117/12.655779
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

As a result of the advances in skin imaging technology and the development of suitable image processing techniques, during the last decade, there has been a significant increase of interest in the computer-aided diagnosis of skin cancer. 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 useful features in dermoscopic diagnosis is the blue-white veil (irregular, structureless areas of confluent blue pigmentation with an overlying white "ground-glass" film) which is mostly associated with invasive melanoma. In this preliminary study, a machine learning approach to the detection of blue-white veil areas in dermoscopy images is presented. The method involves pixel classification based on relative and absolute color features using a decision tree classifier. Promising results were obtained on a set of 224 dermoscopy images.

Citation Download Citation

M. Emre Celebi, Hassan A. Kingravi, Y. Alp Aslandogan, and William V. Stoecker "Detection of blue-white veil areas in dermoscopy images using machine learning techniques", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61445T (17 March 2006); https://doi.org/10.1117/12.655779

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