Heart diseases seriously threaten people's health. More and more functional evaluation of cardiac right ventricle has been considered in the clinical diagnosis in addition to the classical functional evaluation of cardiac left ventricle. It is very important to evaluate the functional parameters of right ventricle in clinical heart disease diagnosis, especially when the ejection fraction of left ventricle is very low. Right ventricular segmentation is needed for the functional evaluation. However, right ventricular segmentation has been difficult due to its thin myocardium, complex structure and significant individual variability. Cine cardiac magnetic resonance image is a golden standard in clinical functional evaluation of cardiac ventricle. In the present paper, we summarize the classic segmentation approaches, evaluation methods and their development, which can help the researchers in the related field have a quick and basic understanding to the right ventricle segmentation.
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.
