Due to the high spatiotemporal resolution , cardiac cine magnetic resonance imaging (CCMRI) has been widely used to evaluate the cardiac function of cardiovascular diseases such as myocardial ischemia and so on. Segmentation-based motion tracking of left myocardium is very important for comprehensive evaluation of cardiac function in the diagnosis and treatment of cardiovascular diseases. However, it is a challenge to track motion of left myocardium, which is homogeneous and cannot provide effective motion information. In this paper, CCMRI imaging techniques for myocardial motion tracking are introduced firstly. Then approaches for motion tracking of left myocardium based on CCMRI image are described in details and are summarized and prospected at the end, which not only helps beginners to have a quick and comprehensive understanding on this topic, but also provides theoretical reference to related researchers for further optimization of approaches for motion tracking of left myocardium. From the current study, motion tracking approaches for left myocardium based on CCMRI image make comprehensive use of the spatiotemporal motion characteristics of CCMRI image, the motion and structures of myocardium of left ventricle and so on, which can make up for the shortcomings of sparse motion information of CCMRI image. However, it still needs improved constraint framework, verification methods and so on.
Mild cognitive impairment (MCI) is a clinical transition state between age-related cognitive decline and dementia. Researchers can use neuroimaging and neurophysiological techniques to obtain structural and functional information about the human brain. Using this information researchers can construct the brain network based on complex network theory. The literature on graph theory shows that the large-scale brain network of MCI patient exhibits small-world property, which ranges intermediately between Alzheimer's disease and that in the normal control group. But brain connectivity of MCI patients presents topologically structural disorder. The disorder is significantly correlated to the cognitive functions. This article reviews the recent findings on brain connectivity of MCI patients from the perspective of multimodal data. Specifically, the article focuses on the graph theory evidences of the whole brain structural and functional and the joint covariance network disorders. At last, the article shows the limitations and future research directions in this field.