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Haemoglobin distribution in ulcers for healing assessment

机译:溃疡中的血红蛋白分布以进行愈合评估

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Wounds that do not follow a predictable course of healing within a specified period of time develop into ulcers causing severe pain and discomfort to the patients. One of the most prominent changes during wound healing is the colour of the tissues. Describing the tissues in terms of percentages of each tissue colour is an approved clinical method of wound healing assessment. The growth of the red granulation tissue marks the beginning of ulcer healing. Granulation tissue appears red in colour due to haemoglobin content in the blood capillaries. An approach based on utilizing haemoglobin content in chronic ulcers as an image marker to detect the growth of granulation tissue is investigated in this study. Independent Component Analysis is employed to extract grey-level haemoglobin images from RGB colour images of chronic ulcers. Extracted haemoglobin images indicate areas of haemoglobin distribution reflecting detected regions of granulation tissue. Data clustering techniques are implemented to classify and segment detected regions of granulation tissue from the extracted haemoglobin images. Results obtained indicate that the developed algorithm performs fairly well with an average sensitivity of 88.24% and specificity of 98.82% when compared to the dermatologist's assessment. The ultimate aim of this research work is to develop an objective non-invasive wound healing assessment system capable of evaluating the healing status of chronic ulcers in a more precise and reliable way.
机译:在指定的时间段内未遵循可预测的愈合过程的伤口会发展为溃疡,从而导致患者严重疼痛和不适。伤口愈合过程中最显着的变化之一就是组织的颜色。用每种组织颜色的百分比描述组织是伤口愈合评估的公认临床方法。红色肉芽组织的生长标志着溃疡愈合的开始。由于毛细血管中的血红蛋白含量,肉芽组织显示为红色。在这项研究中,研究了一种基于利用慢性溃疡中的血红蛋白含量作为图像标记来检测肉芽组织生长的方法。独立成分分析用于从慢性溃疡的RGB彩色图像中提取灰度级血红蛋白图像。提取的血红蛋白图像表示血红蛋白分布区域,反映了肉芽组织的检测区域。实施数据聚类技术以根据提取的血红蛋白图像对肉芽组织的检测区域进行分类和分段。获得的结果表明,与皮肤科医生的评估结果相比,开发的算法性能相当好,平均灵敏度为88.24%,特异性为98.82%。这项研究工作的最终目的是开发一种客观的无创伤口愈合评估系统,该系统能够以更精确和可靠的方式评估慢性溃疡的愈合状况。

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