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Automatic segmentation of skin cancer images using adaptive color clustering

机译:使用自适应颜色聚类自动分割皮肤癌图像

摘要

This paper presents the development of an adaptive image segmentation algorithm designed for the identification of the skin cancer and pigmented lesions in dermoscopy images. The key component of the developed algorithm is the Adaptive Spatial K-Means (A-SKM) clustering technique that is applied to extract the color features from skin cancer images. Adaptive-SKM is a novel technique that includes the primary features that describe the color smoothness and texture complexity in the process of pixel assignment. The A-SKM has been included in the development of a flexible color-texture image segmentation scheme and the experimental data indicates that the developed algorithm is able to produce accurate segmentation when applied to a large number of skin cancer (melanoma) images.
机译:本文介绍了一种自适应图像分割算法的开发,该算法旨在识别皮肤镜图像中的皮肤癌和色素性病变。该算法的关键部分是自适应空间K均值(A-SKM)聚类技术,该技术用于从皮肤癌图像中提取颜色特征。 Adaptive-SKM是一种新颖的技术,包括描述像素分配过程中颜色平滑度和纹理复杂度的主要功能。 A-SKM已包括在灵活的颜色纹理图像分割方案的开发中,实验数据表明,该算法在应用于大量皮肤癌(黑色素瘤)图像时能够产生准确的分割。

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