补充黑色素瘤诊断深色皮肤肤色梯度

V. ZeIjkovic, C. Druzgalski, S. Bojic-Minic, C. Tameze, P. Mayorga
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引用次数: 11

摘要

黑色素瘤是皮肤色素细胞中与黑色素细胞相关的大多数恶性肿瘤之一,是黑色素细胞恶性转化的结果。由于神经细胞嵴的迁移,黑色素瘤不仅可以发生在皮肤上,还可以发生在口腔和生殖器粘膜,以及胃肠道和大脑。黑色素瘤通常存在,表现为颜色、大小、轮廓和形态的变化,也可能出现新的色素病变。特别是,黑色素瘤是美国第六大恶性肿瘤,在非白种人中死亡率高得多,尽管在白人中更为常见。考虑到它的复杂性,即使对经验丰富的皮肤科医生来说,黑色素瘤的临床诊断也是具有挑战性的。这就是为什么有必要开发针对黑肤色和白皙皮肤的黑色素瘤检测的计算机辅助诊断工具,在定量测量的基础上增加更多的客观判断。因此,利用包括各种皮肤癌表现的图像在内的数据库开发和测试了专门的算法。这些诊断指标是利用常用的ABCDE标准对不同肤色进行评估的,同时也利用自然和模拟的深色背景来反映与不同种族群体相关的深色肤色。结合Canny, Prewitt, Roberts和Sobel边缘检测器,可以优化黑色素瘤对深肤色的诊断,并评估反映不同肤色的ABCDE标准的正确分类程度。
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Supplemental melanoma diagnosis for darker skin complexion gradients
Melanoma represents one of most malignant tumors associated with melanocytes in pigmented cells of the skin and in particular is a result of malignant transformation of melanocytes. Due to migration of neural cell crest, melanoma can develop not only on skin, but on oral and genital mucosa, and also gastrointestinal tract and brain. Melanoma is usually present and manifests itself with changes in color, size, contour and configuration, or may occur as new pigmented lesions. In particular, melanoma represents the sixth leading cause of malignancy in the United States with much higher mortality rate among non-Caucasian population, although is more common among whites. Considering its complexity, clinical diagnosis of melanoma is challenging even for experienced dermatologists. This is why it is necessary to develop computer assisted diagnostic tool for melanoma detection focused on dark and fair complexion skin which adds more objective judgments based on quantitative measures. Therefore, specialized algorithms were developed and tested utilizing databases including images of a variety of skin cancer manifestations. Those diagnostic indicators were assessed utilizing commonly used ABCDE criteria for different skin complexions and also natural and simulated darker background reflecting darker skin tones associated with different ethnic groups. Incorporated Canny, Prewitt, Roberts and Sobel edge detectors allowed to optimize melanoma diagnosis for darker skin tones and assess the degree of correct classification for each of ABCDE criterion reflecting varied skin complexion.
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