3D Medical Image Registration

The appearance of different kinds technology of imaging makes people easy to observe Dissection structure of human body. It is very helpful, but information of image that receives from the same human body is difference and complement to another. To make full use of a large amount of information, we must come to explain and utilize them as a whole, it is very important and useful in clinical diagnosis.The registration in medical image is an important technology in the medical image processing, it is a multi-disciplinary research fields that crosses information science, image technology of the computer and medical Science. The present medical image registration can be divided into methods based on the grey levels and methods based on characteristic of the image.This paper discusses registration by maximization of mutually information and surface based image registration, these two kinds methods are mostly used3D registration method in clinic.In the thesis, we first discuss registration by maximization of mutually information. It is fully automatic and images involved in registration don't need any pre-treat. We discuss principle of registration by maximization of mutual information at aspect of entropy and mutual information. We emulate key points involved in registration by maximization of mutually information in detail, such as transformation, interpolation methods and optimization procedure etc. We analyse the impact of PV on mutual information. In order to improve speed, we use many skills to raise speed, such as multi-resolution, reduction of grey levels and Hybrid Powell and Simulated Annealing optimization Algorithm etc, experiment shows that it is valuable to avoid local extremum.Then, we discuss the surface based registration, explain the principle of registration based on surface and enumerate the main points involved in surface based registration. We extract the contour by canny algorithm, discuss Quatemions and SVD which is used in the points-based registration, and Iterative Closest Points algorithm which is frequently used Iterative algorithm. In order to raise speed, we use multi-scale iterative algorithm.