In the present days, cancer has become a menacing disease. Lung cancer is the foremost cancer affecting both men and women throughout the world. In this regard, biomedical imaging is a technology that aids fundamental medical investigations. Some of the widely applied biomedical imaging techniques are Computed Tomography (CT), Magnetic Resonance Imaging (MRI), etc. Among the imaging techniques, CT images are generally used for detecting life frightening pathologies. CT images present high spatial resolution including contrast deviation in tissue. However, CT images are prone to Gaussian noise due to thermal energy fluctuations. Also CT images get affected by artifact and structural noise which hamper correct diagnosis. To overcome this problem, different de-noising filters like Median filter, Gaussian filter, Box filter, Average filter, X-filter are applied on CT images before further processing. In order to identify the superlative filter metrics like SNR (Signal to Noise Ratio) and PSNR (Peak Signal to Noise Ratio) are used. The CT image dataset in (Digital Imaging and Communications in Medicine) DICOM format provided by the (Lung Image Database Consortium) LIDC has been utilized to perform the analysis in the present work.

CT, SNR, PSNR , Filter, DICOM

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