Medical Image Analysis of Image Segmentation and Registration Techniques

摘要

Medical Image Analysis is essential in order to detect and diagnose the various types ofCancers. In recent years there is a rise in the death rate of patients suffering from brain cancer andlung cancer. The chances of survival among people can increase if the detection is done in the earlierstage. The widely used diagnose technique is Magnetic Resonance Imaging (MRI), ComputedTomography (CT) Images which are used to present the cancer location in the brain and lungs. In thiswork the brain tumour and lung cancer is detected and registered through the medical images in threestages. First is the pre -processing stage, a set of medical images is filtered for removing noise by Gaussianfilter, Secondly the image is segmented automatically using Otsu and KNN clustering. Edge Detectionmethod is done by using canny detection method. Third stage is the feature extraction stage, in this stagethe segmented MRI and CT images are registered to obtain the tumour. The feature detection methodsused are the SIFT and SURF algorithm for both brain and lung images to obtain effective results. TheSIFT and Affine Transform registration technique used increases the speed and reduces the complexity ofgeometrical alignments of two images that is the reference and sensed images. It also displays the minutedifference between two identical images rapidly and accurately which is essential for medical diagnoses.