| Heart disease has seriously affected the life and health of people.According to the relative medical research,physiological and pathological information of heart can be reflected by the structure of cardiac fibers.Magnetic resonance diffusion-weighted imaging is one of the most important ways to map the human heart with non-invasiveness.At present,most fiber reconstruction algorithms are based on the structure of human brain and there are less research on human cardiac fibers.This article focuses on Non-Stationary Measure(NSM)of vector data and proposes a new fiber reconstruction method based on NSM and Fast Marching Method(FMM).Two experiments are designed for the sake of improving the new method with simulation data and real heart data.Firstly,this article introduces the principle of diffusion magnetic resonance tensor imaging.The diffusion tensor image is calculated with multi-directional diffusion weighted image based on the principle.The methods of calculation and visualization of tensor correlation measurements are given for the study of fiber reconstruction and NSM.Secondly,the study of NSM in vector data is introduced.The concept of NSM can be applied to various types of data after expansion and the method of NSM calculation on vector data presents in the paper.The NSM of vector data is compared with two methods,Statistical Feature and Minimum Vector Dispersion,which proves that the NSM performs well in noisy conditions.Finally,a new fiber reconstruction method based on NSM and FMM is proposed.In the process of constructing the time field,the solution of the static Hamilton-Jacobi equation is improved to make the time field more accurate.The adaptive coefficient of the velocity function is constructed by the NSM,which makes the improved velocity function consistent with the features of human cardiac fibers.In the simulation experiment and heart data experiment,the improved algorithm can effectively keep the local parallelism of cardiac fibers and control the fiber direction. |