A novel pipeline for detecting lung cancer in initial stage from Computer Tomograpy (CT) scan images.
Abstract:
The second leading cause of death is cancer. From this large domain of cancer, lung cancer is one of the main reasons for death in the world among both men and women, with an impressive rate of about five million deadly cases per year. Every year more than 2,00,000 cases are found in US. Because of high quantity data in CT images and blurred boundaries, tumor segmentation and classification is very hard. In MR images, the amount of data is too much for manual interpretation and analysis. At a very early stage, cancer is not being found because of the small size of the nodules and location of the glands. Machine Learning makes the diagnosis process easier and deterministic. This work has introduced one automatic lung cancer detection method to increase the accuracy and yield and decrease the diagnosis time. The main objective of this work is to detect the cancerous lung nodules from a given input lung image and to predict the lung cancer using Deep Learning technique more efficiently than the existings
