基于频域和空域显著性的色素性皮肤病变分割
Frequency and Spatial domain based Saliency for Pigmented Skin Lesion Segmentation
摘要：
由于皮肤镜图像中存在伪影、病灶与边界对比度低、颜色杂色、病灶边界模糊以及背景不均匀等问题，皮肤病灶分割是一项具有挑战性的任务。在本文中，我们提出了一个简单而有效的基于显着性的方法，在频率和空间域派生的色素性皮肤病变检测。两个颜色模型用于这些地图的建设。我们建议一个不同的度量为每个颜色模型设计地图在空间域中通过颜色特征。频域中的映射是从聚合图像生成的。我们采用一个单独的融合方案，结合各自领域的显着特征。最后，两阶段的显着性集成计划的设计，结合这些地图使用像素乘法。在PH2和ISIC 2016数据集上评估了所提出方法的性能。实验结果表明，该方案产生更好的分割结果相比，国家的最先进的方法。
英文摘要：
Skin lesion segmentation can be rather a challenging task owing to the presence of artifacts, low contrast between lesion and boundary, color variegation, fuzzy skin lesion borders and heterogeneous background in dermoscopy images. In this paper, we propose a simple yet effective saliency-based approach derived in the frequency and spatial domain to detect pigmented skin lesion. Two color models are utilized for the construction of these maps. We suggest a different metric for each color model to design map in the spatial domain via color features. The map in the frequency domain is generated from aggregated images. We adopt a separate fusion scheme to combine salient features in their respective domains. Finally, two-phase saliency integration scheme is devised to combine these maps using pixelwise multiplication. Performance of the proposed method is assessed on PH2 and ISIC 2016 datasets. The outcome of the experiments suggests that the proposed scheme generate better segmentation result as compared to state-of-the-art methods.
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