Nevus atypical pigment network distinction and irregular streaks detection in skin lesions images

Karol Kropidlowski, Marcin Kociolek, M. Strzelecki, Dariusz Czubinski
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引用次数: 6

Abstract

There is no suitable golden standard for the detection of atypical pigment network and irregular streaks applied to skin lesion images. This information however is important in assessment of melanoma in skin dermatoscopic images. Thus there is a need for development of image analysis techniques that satisfy at least subjective criteria defined by dermatologists. In this paper we present the application of histogram based features for detection of atypical pigment network and shape based features supplemented by artificial neural network for detection of irregular streaks. Preliminary test results are promising, for analyzed melanoma images we get 97,7% correctly detected pigmentation networks and 94,8% correctly detected irregular streaks. This paper constitutes the part of our efforts to implement the ELM 7-point checklist in order to support melanoma diagnosis and to automate this process.
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皮肤病变图像中非典型色素网络的区分与不规则条纹的检测
对于皮肤病变图像中不典型色素网络和不规则条纹的检测,目前还没有合适的金标准。然而,这一信息对于皮肤镜图像中黑色素瘤的评估是重要的。因此,有必要发展图像分析技术,至少满足皮肤科医生定义的主观标准。本文提出了基于直方图特征的非典型色素网络检测和基于形状特征的人工神经网络辅助检测不规则条纹的应用。初步的测试结果是有希望的,对于分析的黑色素瘤图像,我们可以正确地检测出97,7%的色素沉着网络和94,8%的不规则条纹。本文是我们努力实施ELM 7点检查表的一部分,以支持黑色素瘤的诊断并使这一过程自动化。
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