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CIELAB based system for burn depth estimation

机译:基于CIELAB的燃烧深度估算系统

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摘要

Successful cure of a burn injury depends highly on the first treatment. Burn depth is traditionally defined in three degrees. Estimation of depth degree is carried out by visual evaluation of the wound by the specialized dermatological experts. This type of evaluation includes a high degree of subjectivity. In the literature it can found objective methods for determining the depth of the burn by processing of digital photographic images. However, these methods estimate only one degree per burn wound despite the fact that it is common to find all three types within the same burn wound. In this paper a classification system to estimate the different depth degrees that a burn wound can present, is proposed. A color characterization algorithm is initially applied to the photographic images. A color and texture features extraction based on the L*a*b* color space and the chromatic opponent channels is carried out. The classifier used is a Fuzzy-ARTMAP neural network. This neural network performs a pixel-based classification to estimate the different depth degrees present in burn wound image. The system has been tested with 60 images. A success rate of around 80% has been achieved.
机译:烧伤的成功治愈很大程度上取决于第一种治疗方法。传统上,燃烧深度定义为三度。深度程度的评估是由专业的皮肤科专家通过视觉评估伤口来进行的。这种评估包括高度的主观性。在文献中可以找到通过处理数字摄影图像来确定烧伤深度的客观方法。但是,尽管通常会在同一烧伤伤口中找到所有三种类型,但这些方法估计每个烧伤伤口只有一个度。在本文中,提出了一种分类系统来估计烧伤可能存在的不同深度。颜色表征算法最初应用于摄影图像。基于L * a * b *颜色空间和彩色对手通道进行颜色和纹理特征提取。使用的分类器是Fuzzy-ARTMAP神经网络。该神经网络执行基于像素的分类,以估计烧伤创面图像中存在的不同深度度。该系统已通过60张图像测试。已达到约80%的成功率。

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