Duzce Vocational School, Duzce University, Düzce, Turkey.
Sakarya University of Applied Science, Geyve/Sakarya, Turkey.
Med Biol Eng Comput. 2020 Nov;58(11):2711-2723. doi: 10.1007/s11517-020-02248-z. Epub 2020 Aug 31.
Early detection of melanoma has critical importance for the success of the treatment. However, a successful early diagnosis is only possible with the existence of discriminative features. In this study, a new descriptor based on the number of colors was developed in order to successfully diagnose lesions of melanoma. The number of colors is the main feature in the identification of melanoma-type skin lesions. The user must select a threshold value when calculating the number of colors of the lesion. The incorrect threshold value selection of non-expert users disrupts the aforementioned feature and also leads to significant diagnostic errors. In this study, it was revealed that color counting threshold values have a significant effect on the distinctiveness of the number of colors. In the three dermoscopic databases, color counting threshold values that provide the maximum distinctiveness on melanoma and benign lesions were determined as 0 and 0.123 respectively. By using these color counting threshold values, the number of colors for each sample in the data sets was calculated separately. Following that, a novel attribute called the number of color difference was defined as a function of color counting threshold values. Experiments using only the proposed new descriptor yielded 52.7% higher f-measure and 84.5% higher true-positive performance than the number of colors used in the literature. The results obtained in this study revealed the importance of accurately determining the number of colors the lesions had and states that the applied color counting threshold significantly influences the classification results. Thereby, a new method is proposed for determining the critical color counting threshold. We claim that the classical ABCD rule should be improved by our new descriptor. Graphical abstract Fig. 1 Selection of threshold has vital effect on skin lesion classification. A new method to select the correct threshold value and a new attribute for correct classification were developed.
早期发现黑色素瘤对治疗的成功至关重要。然而，只有存在有区别的特征，才能实现成功的早期诊断。在这项研究中，开发了一种基于颜色数量的新描述符，以便成功诊断黑色素瘤病变。颜色数量是识别黑色素瘤样皮肤病变的主要特征。用户在计算病变的颜色数量时必须选择一个阈值。非专家用户选择不正确的阈值会破坏上述特征，并导致严重的诊断错误。在这项研究中，发现颜色计数阈值对颜色数量的独特性有显著影响。在三个皮肤镜数据库中，确定黑色素瘤和良性病变的颜色计数阈值分别为 0 和 0.123，以提供最大的独特性。通过使用这些颜色计数阈值，分别计算数据集每个样本的颜色数量。然后，定义了一个新的属性，称为颜色差异数量，作为颜色计数阈值的函数。仅使用所提出的新描述符进行的实验比文献中使用的颜色数量产生了 52.7%更高的 f 值和 84.5%更高的真阳性性能。本研究的结果表明准确确定病变颜色数量的重要性，并指出应用的颜色计数阈值会显著影响分类结果。因此，提出了一种确定关键颜色计数阈值的新方法。我们声称，经典的 ABCD 规则应通过我们的新描述符进行改进。
