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Lung Cancer Detection Using Image Processing Techniques

机译:使用图像处理技术检测肺癌

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Recently, image processing techniques are widely used in several medical areas for image improvement in earlier detection and treatment stages, where the time factor is very important to discover the abnormality issues in target images, especially in various cancer tumours such as lung cancer, breast cancer, etc. Image quality and accuracy is the core factors of this research, image quality assessment as well as improvement are depending on the enhancement stage where low pre-processing techniques is used based on Gabor filter within Gaussian rules. Following the segmentation principles, an enhanced region of the object of interest that is used as a basic foundation of feature extraction is obtained. Relying on general features, a normality comparison is made. In this research, the main detected features for accurate images comparison are pixels percentage and mask-labelling.
机译:近年来,图像处理技术已广泛用于多个医学领域,用于早期检测和治疗阶段的图像改善,其中时间因素对于发现目标图像中的异常问题非常重要,尤其是在诸如肺癌,乳腺癌等各种癌症肿瘤中图像质量和准确性是这项研究的核心因素,图像质量评估和改进取决于增强阶段,在该阶段,基于高斯规则内的Gabor滤波器使用了低预处理技术。遵循分割原理,获得了感兴趣对象的增强区域,该区域被用作特征提取的基本基础。依靠一般特征,进行正态比较。在这项研究中,用于精确图像比较的主要检测特征是像素百分比和蒙版标签。

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