Sadeghi Maryam, Lee Tim K, McLean David, Lui Harvey, Atkins M Stella
School of Computing Science, Simon Fraser University, Canada.
Med Image Comput Comput Assist Interv. 2012;15(Pt 1):298-306. doi: 10.1007/978-3-642-33415-3_37.
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%.
对于皮肤镜结构的自动检测和分析以及皮肤镜图像中条纹等恶性线索的需求日益增加,以实现对致命黑色素瘤的计算机辅助早期诊断。本文提出了一种用于皮肤镜图像中条纹检测和可视化的新方法。我们通过脊线和谷线估计来处理条纹检测。应用方向估计和校正来检测低对比度和模糊的条纹线,并使用候选条纹将300张皮肤镜图像分类为无条纹或有条纹,其曲线下面积(AUC)为90.5%。我们的方法还可以使用检测到的线性结构来检测规则条纹的星爆模式,准确率为81.5%,AUC为87.7%。