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引用次数: 17

摘要

恶性黑色素瘤是所有皮肤癌中最致命的一种。幸运的是,如果及早发现,即使是恶性黑色素瘤也可能成功治疗。本文提出了一种新的黑色素瘤良恶性病变智能分类方法。作为图像分析的第一步,使用预处理技术,通过中值滤波等滤波器去除图像中的噪声和不需要的结构。分割是肿瘤自动检测的重要步骤之一,对检测结果有很大的影响。第二步,采用简单的阈值分割方法对病灶进行分割和定位,并采用边界跟踪算法对分割结果进行验证。第三步,从分割后的图像中提取不同的特征,并使用Stolz算法进行分类。
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Characterization of skin lesions
Malignant melanoma is the deadliest form among all skin cancers. Fortunately, if detected early, even malignant melanoma may be treated successfully. In this paper, a new intelligent method of classifying benign and malignant melanoma lesions is used. As the first step of the image analysis, preprocessing techniques are used to remove noise and undesired structures from the images using filter such as median filtering. Segmentation is one of the important steps in cancer automatic detection, because it can greatly affect on the results of detection. In the second step, a simple thresholding method is used to segment and localize the lesion, a boundary tracing algorithm is also implemented to validate the segmentation. In the third step, the different features are extracted from a segmented image and classified by using Stolz algorithm.
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