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Image Analysis Model For Skin Disease Detection: Framework

机译:皮肤疾病检测的图像分析模型:框架

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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.
机译:皮肤病是世界上最常见的疾病。皮肤病的诊断需要皮肤科医生的高度专业知识和准确性,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。已经进行了许多研究来帮助检测皮肤疾病,例如皮肤癌和肿瘤皮肤。但是,由于以下原因,对疾病的准确识别非常具有挑战性:病变和皮肤之间的对比度低,疾病与非疾病区域之间的视觉相似性等。本文旨在从皮肤图像中检测皮肤疾病并对此进行分析。通过应用滤镜去除噪点或不需要的东西,将图像转换为灰色以帮助处理并获得有用的信息,从而获得图像。这有助于为任何类型的皮肤病提供证据并说明紧急情况。这项研究的分析结果可以帮助医生帮助初步诊断和了解疾病的类型。那与皮肤兼容并且避免副作用。

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