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Image Enhancement and Lung Cancer Detection Using Anisotropic Diffusion Filter

Dhinakaran M., Anushka Mishra, Anshuman Singh, Ankit Pal

Abstract


The leading cause of cancer-related deaths globally is lung cancer. According to the Global Cancer Statistics lung cancer is the leading cause of cancer-related fatalities with 1.8 million deaths and 2.1 million new cases. Early detection of a tiny tumor can stop cancer from spreading and greatly enhance prognosis and survival rates. Consequently, the creation of a sophisticated computer-aided diagnosis system (CADS) may be advantageous for the early therapy of lung cancer. The most frequently
employed imaging method for lung scans is volumetric thoracic computed tomography (CT). However, CT provides good classification detection, is less expensive, has a quick turnaround on imaging, and is widely available. The number of fatalities can be decreased by treating people with lung cancer as soon as it is discovered. This study's main goal is to develop an image processing technique to use image segmentation algorithms to separate CT scan pictures of lung cancer. And anisotropic filter is used to improve the quality of image for better analysis and morphological operation is applied to CT scan to detect the exact location of cancer infected tissue and clear segmentation of inflected region. Proposed method gives good results in terms of better PSNR and MSE value and with increased accuracy.


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References


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