Computer Aided Diagnosis (CAD) for Segmentation and Classification of Burnt Human skin

Ateeq Ur Rehman Butt, Waqar Ahmad, Rehan Ashraf, M. Asif, S. Cheema
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引用次数: 10

Abstract

Human Skin Burn injuries are viewed as the most genuine general medical issue because of which numerous patients died every year all around the globe. Pakistan is a Low-Income Country (LIC) and death rate due to burn injuries is much greater in such countries. To classify burn depths is an under-researched area in Pakistan and has got the great attention of researchers and practitioners. One of the significant issues coming in the Health centers is that Non-Expert doctors are not ready to recognize the burnt area of skin which isn't obvious by bare eyes and hence can't make on the spot decision for correct first treatment according to burn depths, and this may cause a noteworthy issue later on. The objective of this paper is to identify the depth of burnt human skin and to analyze the burns by classifying among first, second and third-degree burns. In this regard, we used the Otsu method of thresholding for segmentation and then applied the statistical method to obtain the feature vector. The maximum average accuracy obtained by using multiple classifiers is reported round about 74.86%. The obtained results will help nonexpert doctors to make on the spot decision by evaluating between first, second and third-degree burns and correct first treatment. The dataset (Images of Burnt Patients) for segmentation and analysis of burnt human skin have been collected from the burn center of Allied Hospital Faisalabad, Pakistan.
烧伤皮肤分割与分类的计算机辅助诊断
人体皮肤烧伤被认为是最真实的一般医学问题,因为全球每年都有许多患者死亡。巴基斯坦是一个低收入国家(LIC),在这些国家,烧伤造成的死亡率要高得多。烧伤深度分类在巴基斯坦是一个研究不足的领域,受到了研究人员和从业人员的高度关注。健康中心出现的一个重要问题是,非专业医生没有准备好识别肉眼看不明显的皮肤烧伤区域,因此无法根据烧伤深度当场决定正确的第一次治疗,这可能会导致一个值得注意的问题。本文的目的是通过一度、二度和三度烧伤的分类来识别烧伤的深度并对烧伤进行分析。对此,我们使用阈值分割的Otsu方法进行分割,然后应用统计方法获得特征向量。据报道,使用多个分类器获得的最大平均准确率约为74.86%。获得的结果将帮助非专业医生通过评估一、二、三度烧伤和正确的第一次治疗来做出现场决策。用于分割和分析烧伤人体皮肤的数据集(烧伤患者图像)来自巴基斯坦费萨拉巴德联合医院烧伤中心。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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