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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) >Impact of various color LED flashlights and different lighting source to skin distances on the manual and the computer-aided detection of basal cell carcinoma borders
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Impact of various color LED flashlights and different lighting source to skin distances on the manual and the computer-aided detection of basal cell carcinoma borders

机译:各种颜色的LED手电筒和不同的光源对皮肤距离的影响对人工和计算机辅助的基底细胞癌边界的检测

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摘要

Background/aims: Quantitative analysis based on digital skin image has been proven to be helpful in dermatology. Moreover, the borders of the basal cell carcinoma (BCC) lesions have been challenging borders for the automatic detection methods. In this work, a computer-aided dermatoscopy system was proposed to enhance the clinical detection of BCC lesion borders. Methods: Fifty cases of BCC were selected and 2000 pictures were taken. The lesion images data were obtained with eight colors of flashlights and in five different lighting source to skin distances (SSDs). Then, the image-processing techniques were used for automatic detection of lesion borders. Further, the dermatologists marked the lesions on the obtained photos. Results: Considerable differences between the obtained values referring to the photographs that were taken at super blue and aqua green color lighting were observed for most of the BCC borders. It was observed that by changing the SSD, an optimum distance could be found where that the accuracy of the detection reaches to a maximum value. Conclusion: This study clearly indicates that by changing SSD and lighting color, manual and automatic detection of BCC lesions borders can be enhanced.
机译:背景/目的:基于数字皮肤图像的定量分析已被证明对皮肤病学有帮助。此外,基底细胞癌(BCC)病变的边界对于自动检测方法而言是具有挑战性的边界。在这项工作中,提出了一种计算机辅助皮肤镜检查系统,以增强对BCC病变边界的临床检测。方法:选择50例BCC病例并拍摄2000张照片。使用八种颜色的手电筒和五种不同的光源到皮肤距离(SSD)获得病变图像数据。然后,将图像处理技术用于病变边界的自动检测。此外,皮肤科医生在获得的照片上标记了病变。结果:对于大多数BCC边界,在超级蓝和浅绿色照明下拍摄的照片所获得的值之间存在相当大的差异。据观察,通过改变SSD,可以找到最佳距离,在该距离处,检测的精度达到最大值。结论:这项研究清楚地表明,通过更改SSD和灯光颜色,可以手动和自动检测BCC病变边界。

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