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Detection and Differentiation of Skin Cancer from Rashes

机译:从皮疹中检测和区分皮肤癌

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摘要

Skin cancer is a highly contagious disease that spreads over the human body very rapidly within a short period of time. Skin cancer and rashes may seem to be similar to each other in the eyes of a dermatologist so it is not easy to determine whether the skin is affected by rashes or skin cancer. Rashes are generic terms used by people and doctors to denote the changes in the skin such as skin infections, skin allergies, skin diseases. Dermatologist identifies skin cancer from rashes when skin does not heal over medication for a prolonged period of time and continues to spread rapidly to other parts of the skin meanwhile knowing the differences between rashes and skin cancer can help a person seek the necessary help or avoid anxiety about a noncancerous rash. The objective of the paper is to differentiate skin cancer from rashes and helps in detecting skin cancer in human skin. Pervious researches were successful in classifying the skin cancer types using image classification and this modal detects and differentiates skin cancer images from rashes images by using CNN[Convolutional neural network] and classify the images as skin cancer or rashes. The model is able to classify the image as skin cancer affected image or rashes image and obtained an average accuracy of 80.2% for 20 epochs.
机译:皮肤癌是一种高度传染性的疾病,可在短时间内迅速传播到整个人体。在皮肤科医生的眼中,皮肤癌和皮疹似乎彼此相似,因此要确定皮肤是否受到皮疹或皮肤癌的影响并不容易。皮疹是人们和医生使用的通用术语,表示皮肤的变化,例如皮肤感染,皮肤过敏,皮肤疾病。皮肤科医生从皮疹中识别出皮疹,这是因为皮肤长时间无法用药治愈,并且继续迅速扩散到皮肤的其他部位,同时知道皮疹和皮肤癌之间的差异可以帮助一个人寻求必要的帮助或避免焦虑关于非癌性皮疹。本文的目的是区分皮疹和皮疹,并有助于检测人皮肤中的皮肤癌。以往的研究成功地使用图像分类对皮肤癌类型进行了分类,并且该模式通过使用CNN [卷积神经网络]来检测和区分皮疹图像和皮疹图像,并将图像分类为皮肤癌或皮疹。该模型能够将图像分类为受皮肤癌影响的图像或皮疹图像,并且在20个时期内的平均准确度为80.2%。

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