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Oriented Pattern Analysis for Streak Detection in Dermoscopy Images

机译:面向图案分析的皮肤镜图像中的条纹检测

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There is an increasing demand for automated detection and analysis of dermoscopy structures and malignancy clues such as streaks in dermoscopy images, for computer-aided early diagnosis of deadly melanoma. This paper presents a novel approach for streak detection and visualization on dermoscopic images. We tackle the detection of streaks by means of ridge and valley estimation. Orientation estimation and correction is applied to detect low contrast and fuzzy streaks lines, and candidate streaks are used to classify dermoscopy images into streaks Absent or Present with the AUC of 90.5% on 300 dermoscopy images. Our approach can also detect starburst pattern of regular streaks using detected linear structures with accuracy of 81.5% and AUC of 87.7%.
机译:对于计算机辅助的致命性黑色素瘤的早期诊断,对皮肤镜结构和恶性线索(例如皮肤镜图像中的条纹)的自动检测和分析的需求不断增长。本文提出了一种新颖的方法,用于在皮肤镜图像上进行条纹检测和可视化。我们通过山脊和山谷估计来处理条纹的检测。应用方向估计和校正来检测低对比度和模糊条纹线,并使用候选条纹将皮肤镜检查图像分类为在300幅皮肤镜检查图像上不存在或存在的AUC为90.5%的条纹。我们的方法还可以使用检测到的线性结构检测规则条纹的星爆图案,其准确度为81.5%,AUC为87.7%。

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