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Border Detection of Skin Lesion Images Based on Fuzzy C-Means Thresholding

机译:基于模糊C型阈值的皮肤病变图像的边框检测

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The accurate location of the border of skin lesions is an important first step in the automatic diagnosis of malignant melanoma. In this paper, we propose a new method of segmentation to locate the skin lesion. The method consists to two stages; image pre-processing and image segmentation. As the first step of image analysis, pre-processing techniques are implemented to remove noise and undesired structures for the images using median filtering. In the second step, the fuzzy c-means (FCM) thresholding technique is used to segment and localize the lesion. The border detection results are visually examined by an expert dermatologist and are found to be highly accurate.
机译:皮肤损伤边界的准确位置是自动诊断恶性黑素瘤的重要第一步。在本文中,我们提出了一种新的分段方法来定位皮肤病变。该方法组成了两个阶段;图像预处理和图像分割。作为图像分析的第一步,实现预处理技术以使用中值滤波去除图像的噪声和不期望的结构。在第二步中,模糊C型(FCM)阈值化技术用于分段和定位病变。专家皮肤科医生目视检查边界检测结果,并被发现是高度准确的。

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