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Classification of cervical cancer tissues using a novel low cost methodology for effective screening in rural settings

机译:使用新型低成本方法对宫颈癌组织进行分类以在农村地区进行有效筛查

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Cervical cancer is the second highest killer of women in Sub-Sahara Africa. This is due to unavailability of adequate screening methods and inability to pay where existing methods are available. This work addresses the issue of identifying and classifying cervical cancerous tissues for images taken from a standard camera. A cost effective method is developed for the imaging of cervical cancer in developing countries by analysing images from a standard camera. The image is enhanced using noise reduction and a Canny edge detector algorithm to find the intensity of the edges. Preliminary results obtained from clinical settings and images obtained are analysed by identifying the edges of the tissues of the cervix and classifying them based on the frequency of the edges. The results show above 90% classification accuracy. This shows that image analysis algorithm has the potential to successfully diagnose cervix cancer.
机译:宫颈癌是撒哈拉以南非洲地区女性的第二大杀手。这是由于无法使用适当的筛查方法,以及无法在现有方法可用的情况下付款。这项工作解决了从标准相机拍摄的图像识别和分类宫颈癌组织的问题。通过分析来自标准相机的图像,为发展中国家的宫颈癌成像开发了一种经济有效的方法。使用降噪和Canny边缘检测器算法可以找到边缘的强度,从而增强图像。通过确定子宫颈组织的边缘并根据边缘的频率对它们进行分类,可以分析从临床环境中获得的初步结果和获得的图像。结果显示出超过90%的分类精度。这表明图像分析算法具有成功诊断宫颈癌的潜力。

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