多光谱图像中继发性愈合溃疡的半自动分类

J. Arnqvist, J. Hellgren, J. Vincent
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引用次数: 26

摘要

伤口的特写彩色照片被用作输入。操作者对感兴趣的区域进行标记,生成二值图像。根据伤口的严重程度,选择一个训练好的分类器。将数字图像与二值图像进行分类组合,给出定性(坏死/纤维蛋白和肉芽比例)和定量(伤口大小)参数。通过这种方式,分析大量伤口照片的时间大大减少。该方法已在IMTEC Epsilon图像处理系统上用Pascal语言编写。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semiautomatic classification of secondary healing ulcers in multispectral images
Close-up color photographs of the wounds were used as imput. The interesting areas were marked by the operator, creating a binary image. According to the severity of the wound, one of the trained classifiers was selected. The digital picture was classified and combined with the binary image, giving the qualitative (proportion necroses/fibrin and granulation) and the quantitative (wound size) parameters. In this way the time for analyzing a large number of wound photographs was substantially reduced. The method has been programmed in Pascal on the IMTEC Epsilon image processing system.<>
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