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Computer-aided diagnosis (CAD) of the skin disease based on an intelligent classification of sonogram using neural network

机译:使用神经网络基于超声图的智能分类,对皮肤疾病进行计算机辅助诊断(CAD)

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摘要

Today skin diseases and lesions are the most common diseases that people suffer in different age groups, such as eczema, scalp ringworm, skin fungal, skin cancer of different intensity (basal cell carcinoma and squamous cell carcinoma and melanoma…), diabetic ulcers, and etc. There are different ways to evaluate and diagnose mentioned diseases. For example, most dermatologists prescribe the biopsy to diagnose them. This is a simple method to identify the type of skin disease, but that is an invasive method, and in prolonged time leads to pain and discomfort for patients. Another method that can be used to diagnose is based on non-ionizing radiation such as acoustic or ultrasound waves, which is being investigated in this study. It should be noted that ultrasound imaging is one of the best and useful medical diagnostic tool to scan soft tissue. Therefore, the aim of this study is to diagnose the diseases by studying and analyzing sonography images using intelligent artificial neural network, in order to eliminate any need for radiography and pathobiology process in dermatology. Our main diagnostic tool in this study is a sonography image acquisition system that uses non-ionizing ultrasound waves for skin imaging. Intelligent artificial neural network has been used to study and intelligently classify the skin sonograms. The results of this study show the high capability of this method in diagnosis and classification of the skin diseases.
机译:如今,皮肤疾病和病变是人们在不同年龄段遭受的最常见疾病,例如湿疹,头皮癣,皮肤真菌,不同强度的皮肤癌(基底细胞癌,鳞状细胞癌和黑色素瘤……),糖尿病性溃疡和评估和诊断提到的疾病有不同的方法。例如,大多数皮肤科医生开具活检来诊断它们。这是一种识别皮肤疾病类型的简单方法,但它是一种侵入性方法,长时间会导致患者疼痛和不适。可以用于诊断的另一种方法是基于非电离辐射,例如声波或超声波,本研究正在对此进行研究。应当指出,超声成像是扫描软组织的最佳和有用的医学诊断工具之一。因此,本研究的目的是通过使用智能人工神经网络研究和分析超声图像来诊断疾病,从而消除皮肤病学中的射线照相和病理生物学过程。我们在这项研究中的主要诊断工具是超声图像采集系统,该系统使用非电离超声波进行皮肤成像。智能人工神经网络已用于研究和智能分类皮肤超声图。这项研究的结果表明该方法在皮肤疾病的诊断和分类中具有很高的能力。

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