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Computerized Classification of CT Lung Images using CNN with Watershed Segmentation

机译:利用分水岭分割的CNN对CT肺图像进行计算机分类

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Cancer is a major threat to the lives of human beings. Around 74% of the people who get affected by cancer lost their lives. But early detection of cancer cells can prevent death rates. CT(Computerized Tomography) is one of the major used for cancer cell identifications by the oncologist. Computer-aided cancer detection plays a major role in the detection of cancer in an early stage. Classification of CT scan images comes as the first stage for computer-aided detection of cancer cells. CNN(Convolution Neural Network) based classification method along with Gaussian Filtering and Watershed Segmentation is proposed for effective classification of CT Scan Images.500 CT Scan images of Bone, Brain, Lung, Kidney, Neck are collected from the Oncology Department, Manipal Hospitals, Vijayawada. The accuracy rate of 94.5% is achieved with the proposed CNN based classification CT Scan images.
机译:癌症是对人类生命的重大威胁。约有74%的癌症患者丧生。但是及早发现癌细胞可以防止死亡率。 CT(计算机断层扫描)是肿瘤学家用于癌细胞鉴定的主要方法之一。在早期阶段,计算机辅助癌症检测在癌症检测中起着重要作用。 CT扫描图像的分类是计算机辅助检测癌细胞的第一步。提出了基于CNN(卷积神经网络)的分类方法以及高斯滤波和分水岭分割技术,以对CT扫描图像进行有效分类。从Manipal医院的肿瘤科收集了500枚骨头,脑,肺,肾脏,颈部的CT扫描图像。维杰耶瓦达。提出的基于CNN的分类CT扫描图像可实现94.5%的准确率。

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