A Review of Techniques for Lung Cancer Detection

Abstract

Image processing techniques are widely used in the medical field for image improvement in earlier detection and treatment stages. Here, time factor is crucial to discover the abnormality in target images, especially in cancer tumors such as lung cancer. Image quality and accuracy are the core factors. Image quality assessment and improvement depend on the enhancement stage where a low pre-processing technique is used, which is based on Gabor filter within Gaussian rules. Following the segmentation rules, an enhanced region of the object of interest that is used as the foundation of feature extraction is obtained. It focuses on locating nodules (early symptoms of the diseases), which appear in the patients’ lungs. The aim is to computerizing these selections. The available lung cancer images and its database are passed in three stages: pre-processing, feature extraction and lung cancer cell identification, to achieve higher quality and accuracy in the experimental results.