当前位置: X-MOL 学术Med. Biol. Eng. Comput. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Development of new descriptor for melanoma detection on dermoscopic images.
Medical & Biological Engineering & Computing ( IF 3.2 ) Pub Date : 2020-08-31 , DOI: 10.1007/s11517-020-02248-z
Hasan Akan 1 , Mustafa Zahid Yıldız 2
Affiliation  

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.



中文翻译:

开发用于皮肤镜图像上黑色素瘤检测的新描述符。

黑色素瘤的早期检测对于治疗的成功至关重要。然而,成功的早期诊断只有在存在鉴别特征的情况下才有可能。在这项研究中,开发了一种基于颜色数量的新描述符,以成功诊断黑色素瘤的病变。颜色的数量是识别黑色素瘤型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。非专家用户不正确的阈值选择会破坏上述特征,并且还会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着影响。在三个皮肤镜数据库中,对黑色素瘤和良性病变提供最大区别的颜色计数阈值分别确定为 0 和 0.123。通过使用这些颜色计数阈值,可以分别计算数据集中每个样本的颜色数量。之后,将称为色差数的新属性定义为颜色计数阈值的函数。仅使用提议的新描述符的实验产生了高出 52.7% 一种称为色差数的新属性被定义为颜色计数阈值的函数。仅使用提议的新描述符的实验产生了高出 52.7% 一种称为色差数的新属性被定义为颜色计数阈值的函数。仅使用提议的新描述符的实验产生了高出 52.7%f -measure 和比文献中使用的颜色数量高 84.5% 的真阳性性能。本研究中获得的结果揭示了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着影响分类结果。因此,提出了一种确定临界颜色计数阈值的新方法。我们声称我们的新描述符应该改进经典的 ABCD 规则。

更新日期:2020-10-14
down
wechat
bug