Detection of Lesion of Lung Cancer in CT Scan Images using Watershed Segmentation

This paper presents a lesion of lung cancer detection exist in CT scan images using watershed segmentation. Lung cancer is a disease of uncontrolled cell growth in tissues of the lung. It seems to be the common cause of death among people throughout the world. Therefore, diagnosis of lung cancer at early stage can help doctors to treat patients and keep them alive. The main aim of this research is to establish an image processing method for segmentation of lung cancer from CT scan images by using image processing techniques. In order to achieve the main aims, the work is divided into two parts, first is obtaining lung region from CT scan images and second is detecting the lesion of lung cancer. Hence, this paper will present the outcome of the second part. The lung lobes and nodules or lesion in CT image are segmented using two techniques which are convolution watershed and modified watershed within two stage approaches. Firstly, the image will undergo threshold, clustering and image filtering as well as enhancement process to get better and clearer lung area image. This stage is known as pre-processing stage where this stage is needed to improve the quality of images as the images normally comes with some unwanted information that may obscure some feature that are important. In this stage, the distortion or noise will be removed in order to enhance the important features in the images. Next, is the most important stage in this research which is the segmentation stage since convolution and modified watershed is considered as an essential step in medical image analysis, classification and detecting the lesion of lung cancer. Then, the performance of segmentation process is measured whether or not it improves the accuracy, recall, precision and F- score parameters. The comparative analysis is made on 50 set of images. The outcome of this research is very helpful for the doctor to determine the type of treatment should be provided to the patient. and to diagnose the lung cancer and nodule on the image