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Analysis and comparison of image enhancement techniques for the prediction of lung cancer

机译:图像增强技术在肺癌预测中的分析与比较

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摘要

Presently, lung cancer is identified in 2.6 million people and resulted in 1.8 million deaths. It is the most common type of cancer occurring in men and women. Smoking and air pollution are the main reason for lung cancer. So there is a need for identifying the cancerous cells present in the early stages within a shorter period and provides proper solution. Research work aiming at Image enhancement technique which will help in the detection of lung cancer in the earlier stages. A new technique is proposed to overcome the drawbacks for image enhancement using Gabor Filters, Discrete Wavelet Transform (DWT), and Auto Enhancement Algorithm (AEA). In this article, X-ray lung images are considered and processed using various techniques-Gabor filter, DWT and AEA. For real time analysis, obtained results are comparable with standard values. Hence, this new technique using Gabor filter for Image Enhancement using can be used for immediate detection of cancerous cells in patients.
机译:目前,在260万人中发现肺癌,导致180万人死亡。它是男女中最常见的癌症类型。吸烟和空气污染是肺癌的主要原因。因此需要鉴定在较短时期内早期存在的癌细胞并提供适当的解决方案。针对图像增强技术的研究工作将有助于早期阶段检测肺癌。提出了一种新技术来克服使用Gabor滤波器,离散小波变换(DWT)和自动增强算法(AEA)进行图像增强的缺点。在本文中,将使用多种技术(Gabor滤波器,DWT和AEA)来考虑和处理X射线肺部图像。对于实时分析,获得的结果与标准值相当。因此,使用Gabor滤波器进行图像增强的新技术可用于立即检测患者体内的癌细胞。

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