Automatic lesion boundary detection in dermoscopy images using gradient vector flow snakes
Automatic lesion boundary detection in dermoscopy images using gradient vector flow snakes
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DOI：
10.1111/j.1600-0846.2005.00092.x
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发表时间：
2005-02-01
影响因子：
2.2
通讯作者：
Hvatum, E
中科院分区：
文献类型：
--
作者：
Erkol, B;Moss, RH;Hvatum, E
背景：恶性黑色素瘤如果早期治疗预后良好。色素性病变的皮肤镜图像通常是在低入射角照明下，皮肤浸在玻璃板下的油中，以10倍放大倍数拍摄的。从背景皮肤中准确分割皮肤病变很重要，因为一些预期用于诊断的特征涉及病变的形状，而其他特征涉及病变与周围皮肤颜色相比的颜色。
方法：在这项研究中，对梯度向量流（GVF）蛇模型进行了研究，以寻找皮肤镜图像中皮肤病变的边界。引入了一种自动初始化方法，使皮肤病变边界确定过程完全自动化。
结果：针对70张良性皮肤病变图像和30张黑色素瘤皮肤病变图像，给出了基于GVF的方法和颜色直方图分析技术的皮肤病变分割结果。与皮肤科医生手动分割的病变相比，基于GVF的方法在良性和黑色素瘤图像集上获得的平均误差均低于颜色直方图分析技术。
结论：基于GVF的方法的实验结果表明，它作为一种皮肤镜图像中皮肤病变自动分割技术是有前景的。
Background: Malignant melanoma has a good prognosis if treated early. Dermoscopy images of pigmented lesions are most commonly taken at x 10 magnification under lighting at a low angle of incidence while the skin is immersed in oil under a glass plate. Accurate skin lesion segmentation from the background skin is important because some of the features anticipated to be used for diagnosis deal with shape of the lesion and others deal with the color of the lesion compared with the color of the surrounding skin.Methods: In this research, gradient vector flow (GVF) snakes are investigated to find the border of skin lesions in dermoscopy images. An automatic initialization method is introduced to make the skin lesion border determination process fully automated.Results: Skin lesion segmentation results are presented for 70 benign and 30 melanoma skin lesion images for the GVF-based method and a color histogram analysis technique. The average errors obtained by the GVF-based method are lower for both the benign and melanoma image sets than for the color histogram analysis technique based on comparison with manually segmented lesions determined by a dermatologist.Conclusions: The experimental results for the GVF-based method demonstrate promise as an automated technique for skin lesion segmentation in dermoscopy images.