皮肤病变分析与分类的多尺度方法

Y. Filali, A. Ennouni, M. A. Sabri, A. Aarab
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引用次数: 16

摘要

皮肤癌是世界上最致命的癌症之一。如果不及早诊断,可能很难治愈。提出了一种皮肤镜图像中皮肤损伤自动分割与分类的新方法。该分割基于预处理;利用彩色结构-纹理图像分解将纹理图像分解为纹理和几何分量。几何分量用于病灶分割,纹理分量用于提取病灶纹理特征。特征分类使用支持向量机(SVM)分类器进行。效率和提出的方法的性能进行了评估,与最近和强大的皮肤镜方法从文献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiscale approach for skin lesion analysis and classification
Skin cancer is one of the most deadly cancers in the world. If not diagnosed in early stages it might be hard to cure. This paper suggests a new approach for automatic segmentation and classification of skin lesion for dermoscopic images. The segmentation is based on a pre-processing; using the color structure-texture image decomposition to decompose a textured image into texture and geometrical components. Geometrical component is used in the lesion segmentation and the texture component is used to extract the lesion texture features. Feature classification is performed using the Support Vector Machine (SVM) classifier. The efficiency and the performance of the proposed approach are evaluated in comparison with recent and robust dermoscopic approaches from literature.
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