皮肤病检测的图像分析模型:框架

Alaa Haddad, S. Hameed
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引用次数: 20

摘要

皮肤病是世界上最常见的疾病。皮肤病的诊断对皮肤科医生的专业知识和准确性要求很高,因此提出了计算机辅助皮肤病诊断模型,以提供更客观可靠的解决方案。许多研究都是为了帮助检测皮肤疾病,如皮肤癌和肿瘤皮肤。但由于病变与皮肤对比度低,病变与非病变区域视觉相似等原因,对疾病的准确识别极具挑战性。本文的目的是从皮肤图像中检测出皮肤病,并对该图像进行分析,通过滤波去除噪声或不需要的东西,将图像转换为灰色,以帮助处理并获得有用的信息。这有助于为任何类型的皮肤病提供证据,并说明紧急情况。本研究的分析结果可以帮助医生进行初步诊断,了解疾病的类型。与皮肤相容,避免副作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Analysis Model For Skin Disease Detection: Framework
Skin disease is the most common disease in the world. The diagnosis of the skin disease requires a high level of expertise and accuracy for dermatologist, so computer aided skin disease diagnosis model is proposed to provide more objective and reliable solution. Many researches were done to help detect skin diseases like skin cancer and tumor skin. But the accurate recognition of the disease is extremely challenging due to the following reasons: low contrast between lesions and skin, visual similarity between Disease and non-Disease area, etc. This paper aims to detect skin disease from the skin image and to analyze this image by applying filter to remove noise or unwanted things, convert the image to grey to help in the processing and get the useful information. This help to give evidence for any type of skin disease and illustrate emergency orientation. Analysis result of this study can support doctor to help in initial diagnoses and to know the type of disease. That is compatible with skin and to avoid side effects.
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