A Novel Method for Mining Heterogeneous Lung Cancer from Computer Tomography (CT) Scan
Published: March 03, 2022
DOI: 10.55162/MCMS.02.023
Abstract
Early detection of any type of cancer, especially lung cancer, one of the world’s worst diseases, can save a lot of lives. By using the early forecast, we will be able to increase life expectancy and decrease death. While there are other approaches for detecting lung cancer cells, such as X-rays and CT scans, CT pictures were found to be more preferred. CT scans, for example, use 2D images to get more accurate results. The proposed approach here will cover how to interpret CT pictures from a Computer Tomography (CT) Scan with the Confusion Matrix for Mining Heterogeneous Lung Cancer. This study will look at how image conversion may be performed using various image processing approaches to get better outcomes from CT images. The Confusion Matrix is a tool for calculating inequality in an image pattern. Following Confusion Matrix’s examination of the processed images, a final accuracy of 93 percent is attained.
Keywords: Computer Tomography (CT); Mining; Confusion Matrix; Lung Cancer
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