Machine Learning based Lung Cancer Detection & Analysis

Abstract

The key to treat cancer is early detection. This study has reviewed the fractal image analysis technique for cancer cell detection. Typical abnormalities in cancer cells include uncontrolled cell proliferation. Measurement of morphological complexity and study of figures with atypical shapes are both possible with fractal analysis. Investigations were conducted using simulations of human breast cancer cells. We investigated and compared changes in the fractal dimension between cancer cells and normal cells. The preliminary results demonstrate that the picture based fractal analysis technique is able to locate breast cancer cells. It has a great deal of potential to shed light on the morphological classification of tumor growth and could be used as a marker for early cancer identification and the effectiveness of cancer treatments. The segmentation and data enhancement categorization scheme has been completed. e and The accuracy of lung cancer detection is greater. Cancer can spread to other organs and impair their normal activities, making it a fatal condition. The cancer grows more deadly as it advances in stage. The doctor will do a number of tests to ascertain the degree and seriousness of the disease, and based on the results, the stage of cancer will be determined. Before giving a chance to develop and spread, certain cancers can be detected early. Early cancer discovery results in significantly better treatment outcomes and less physical, emotional, and financial suffering.