An Automatic Identification of Lung Cancer from Different Types of Medical Images

Identification of lung cancer from the medical images is the most difficult task. The objective of this research work is to identify the cancerous and non-cancerous lung which is taken from different medical images like Computer Tomography medical images and Positron Emission Tomography medical images. The proposed algorithm is used to predict lung cancer by using different image processing techniques. It is divided into four stages such as pre-processing, binarization, segmentation and thresholding. This research paper ensures that the image quality is retained effectively thereby extracting appropriate features for identifying cancerous and non-cancerous lung. The algorithm is trained and tested for cancerous and non-cancerous images.