Research On The Applications Of Snake Models In Medical Image Segmentation

As one research branch in the field of computer vision, medical image processing is an important application of computer graphics and digital image processing in the biomedical engineering. Extracting the object's contours from medical images is the foundation of diagnostic and sceince research. Active contour models (ACM) are very suitable to medical image segmentation and contour extracting due to its highly dynamic quality. The primary task of the thesis is to study the key points of applying ACM to solve problems of precessing medical images.The first problem to be solved is how to confirm the initial contour and the parameters of the models. The thesis uses the method of initial contour selection of snake model based on watershed algorithm instead of the method of depicting the contours by manual. Result shows that the algorithm can quickly get the availabe contour that works well in the further process. For the parameters, we get the parameters by estimating the position and energy of non-edge points in the next balance state, so the parameters can be changed adaptively in order to get a better segmentation. Combining the prior knowledge of the medical images to the snake models is one of developing trends. This thesis analyse the characteristic of the medical images and improve the snake models with an extra elliptic force which is computed by elliptic curve fitting, which can maintain contours with the elliptic shapes during the converging process.The experiments followed show that the methods above work well in the medical images and can be easily applied in clinic systems.