论文标题
两种诊断恶性黑色素瘤的分割方法
Two Segmentation Methods for the Diagnosis of Malignant Melanoma
论文作者
论文摘要
自动诊断恶性黑色素瘤高度取决于用于可疑病变的分割方法。我们建议参数选择方法（PSM）和最大面积方法（MAM），以分割要诊断的病变。在此，将这些分割方法与皮肤癌专家的分割和其他三种常规算法进行了比较。根据敏感性，特异性和准确性，比较了基于两种建议的两种常规和专家分割的恶性黑色素瘤的诊断。
Automatic diagnosis of malignant melanoma highly depends on the segmentation methods used for the suspicious lesion. We suggest the parameter selection method (PSM) and maximum area method (MAM) for the segmentation of the lesion to be diagnosed. Herein, these segmentation methods are compared to a skin cancer expert's segmentation and three other conventional algorithms. The diagnosis of malignant melanoma based on the two suggested, three conventional, and expert's segmentation are compared with respect to sensitivity, specificity, and accuracy.
