Magnetic Resonance Image Distortion Correction Method And Application In The Detection Of Myocardial Infarction

In recent ten years, Magnetic Resonance Imaging (MRI) techniques have been developing quickly, and new imaging techniques have kept coming forth. Diffusion tensor imaging (DTI), a new Magnetic Resonance imaging method, has emerged, which utilizes the diffusion tensor of each voxel calculated from multi-direction diffusion weighted image. By imaging the Brownian motion of water molecules, DTI can show information of the structure of tissues and the exchanges of water molecules between tissues in pathology. Medical image registration consists in finding a transformation that realigns two images taken by different sensors or at different times to establish the spatial correspondence between the template image and the study image. When the image registration process finished, the anatomical point in images correspond with each other, which is beneficial for providing the complementary and useful information of different images to improve image-aided in clinical diagnosis and treatment. Medical image registration becomes a very important research topic in the bio-medical engineering domain. The main work in this thesis is as follows:This thesis introduces the concept and framework of medical image registration, analyzes the features of current medical image registration methods. Especially, the two most commonly used methods have been studied, with one based on maximization of mutual information (MI) and another based upon B-spline function.This paper presents a new medical image registration method based on the features of DTI, which have distortions in only one direction. The proposed method included Edge Detection, Affine Transformation and Linear Interpolation steps. The first process in my method is to detect the edges of reference and float images respectively. Since the distortion occurs in phase encoding direction (horizontal direction), and no distortions occurs in reading direction (vertical direction). The start points and endpoints of two images are matched row by row according to the affine transform theory. Simulation results show that the registration performance is improved comprehensively compared with the existing two methods, especially the efficiency. This method is very suitable for DTI.All the images used in this thesis, are acquired from a Siemens Magnetom Tim a Trio 3T MRI machine. After this registration method is utilized, the Apparent Diffusion Coefficient (ADC) can be calculated more accurate, resulting in better image-aided diagnosis of the myocardial infarction.