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皮肤癌的最有效治疗方法是早期诊断加积极有效切除原发灶,对预后和降低死亡率起决定性作用。然而,依靠肉眼对皮肤肿瘤进行诊断,主观性大,即使训练有素的专家其诊断也存在较大的差异。皮肤镜图像计算机辅助诊断系统正是解决这个问题的有效途径,其可以对病变组织自动提取、智能识别,具有定量测量和分析的功能,使诊断更加精确、客观。本文对皮肤镜图像计算机辅助诊断系统的研究现状进行综述,并对皮肤镜图像分析中所涉及的图像质量评价、预处理去噪、皮损分割、特征提取和分类识别等技术进行总结,最后给出未来发展趋势。为此方面的研究人员提供借鉴意义。
Skin cancer is the most effective treatment for early diagnosis plus effective removal of primary lesions, the prognosis and reduce mortality plays a decisive role. However, relying on the naked eye to diagnose skin tumors, subjectivity, even if the diagnosis of well-trained experts there is a big difference. Computer-aided diagnosis system of dermoscopic images is an effective way to solve this problem. It can automatically extract and identify the diseased tissue with the function of quantitative measurement and analysis, making the diagnosis more accurate and objective. This article summarizes the research status of computer aided diagnosis system of dermoscopic images and summarizes the techniques of image quality evaluation, pretreatment denoising, skin lesions segmentation, feature extraction and classification and identification involved in the dermoscopic image analysis, and finally The future trend of development. Provide reference for researchers in this area.