皮损图像分割是基于皮肤镜的辅助诊断系统的关键。与现有基于纹理或颜色的传统特征进行分割的方法不同,提出了一种基于独立色素浓度分布的分割方法。首先基于Lambert-Beer定律建立皮肤镜成像模型,利用独立成分分析方法获得色素浓度分布,并进行可视化显示。然后,把独立色素浓度的比值定义为色素浓度比,该值强化了单一色素浓度在空间的梯度分布。最后,在色素浓度比图上使用全局或局部二值化算法获得最终分割效果。实验结果表明,本文算法具有很好的鲁棒性和通用性,即使原图中皮损区域梯度不明显,也能获得很好的分割效果。

Skin lesion detection plays dominant role in computer-aided diagnosis system of dermoscopic image. Be different from existing segmentation algorithms which are based on traditional features like texture or color, the proposed algorithm is based on independent pigment concentration distribution. First, a dermoscopic imaging model is built based on Lambert-Beer law, followed by obtaining and visualizing pigment concentration distribution after applying ICA method. Then give the definition of Pigment Concentration Ratio(PCR), which puts emphasize on gradient distribution of single pigment concentration. Final segmentation is created by applying global or local thresholding-based algorithm on PCR. Experiments show the robustness and generalization of proposed algorithm. Especially, expected segmentation result is achieved even if lesion regions of input image show very dim gradient.