IMPLEMENTATION OF LUNG CANCER NODULE FEATURE EXTRACTION USING THRESHOLD TECHNIQUE

Abstract: Image Processing and Analysis can be defined as the act of examining images for the purpose of identifying objects and judging their significance.In current days, image processing techniques are widely used in many medical areas for improving earlier detection and treatment stages, especially in various cancer nodules such as the lung cancer, breast cancer, and brain cancer and so on. Segmentation refers to the process of partitioning a digital image into multiple segments known as super-pixels. Image segmentation is typically used to locate objects and boundaries in images. In this work we are uses mean filter and median filter for image preprocessing. For image segmentation, Otsu's thresholding and marker controlled Watershed segmentation approach are used to segment the lung of CT image. The main objective of this paper is to implement lung nodule segmentation and feature extraction using digital image processing for the classification of the disease stages to avoid serious stages early and to reduce lung cancer percentage distribution.

Keywords: Segmentation, Mean filter, median filter, thresholding.