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首页> 外文期刊>Skin research and technology: official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) >Skin tumor area extraction using an improved dynamic programming approach.
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Skin tumor area extraction using an improved dynamic programming approach.

机译：使用改进的动态编程方法提取皮肤肿瘤区域。

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摘要

Border (B) description of melanoma and other pigmented skin lesions is one of the most important tasks for the clinical diagnosis of dermoscopy images using the ABCD rule. For an accurate description of the border, there must be an effective skin tumor area extraction (STAE) method. However, this task is complicated due to uneven illumination, artifacts present in the lesions and smooth areas or fuzzy borders of the desired regions.In this paper, a novel STAE algorithm based on improved dynamic programming (IDP) is presented. The STAE technique consists of the following four steps: color space transform, pre-processing, rough tumor area detection and refinement of the segmented area. The procedure is performed in the CIE L(*) a(*) b(*) color space, which is approximately uniform and is therefore related to dermatologist's perception. After pre-processing the skin lesions to reduce artifacts, the DP algorithm is improved by introducing a local cost function, which is based on color and texture weights.The STAE method is tested on a total of 100 dermoscopic images. In order to compare the performance of STAE with other state-of-the-art algorithms, various statistical measures based on dermatologist-drawn borders are utilized as a ground truth. The proposed method outperforms the others with a sensitivity of 96.64%, a specificity of 98.14% and an error probability of 5.23%.The results demonstrate that this STAE method by IDP is an effective solution when compared with other state-of-the-art segmentation techniques. The proposed method can accurately extract tumor borders in dermoscopy images.
机译：黑色素瘤和其他色素沉着的皮肤病变的边界（B）描述是使用ABCD规则对皮肤镜图像进行临床诊断的最重要任务之一。为了准确描述边界，必须有一种有效的皮肤肿瘤区域提取（STAE）方法。然而，由于光照不均匀，病变区域中存在假象，目标区域的平滑区域或边界模糊，使得该任务复杂化。本文提出了一种基于改进动态规划（IDP）的STAE算法。 STAE技术包括以下四个步骤：颜色空间变换，预处理，粗略的肿瘤区域检测和细分区域的细化。该过程在CIE L（*）a（*）b（*）色彩空间中执行，该色彩空间大致均匀，因此与皮肤科医生的感知有关。在对皮肤病变进行预处理以减少伪影后，通过引入基于颜色和纹理权重的局部成本函数来改进DP算法。在总共100幅皮肤镜图像上测试了STAE方法。为了将STAE与其他最新算法的性能进行比较，将基于皮肤科医生绘制的边界的各种统计量用作基本事实。所提出的方法以96.64％的灵敏度，98.14％的特异性，5.23％的错误概率优于其他方法。结果表明，与其他现有技术相比，IDP的STAE方法是一种有效的解决方案细分技术。所提出的方法可以准确地提取皮肤镜图像中的肿瘤边界。

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