چكيده به لاتين
Cardiovascular diseases are the major causes of death throughout the world. Knowing some information about LV, its shape and some other measures, can be effective in prevention and treatment. The assessment of LV can provides useful information about condition and status of heart. For assessment of some properties in one cardiac cycle, studying some fundamental parameters, such as volume changes over time, relies on accurate delineating LV borders in all frames. Manual segmentation of all frames of one cardiac cycle in different standard echo views, as routinely carried by experts, is tedious and time consuming and necessitates expertise to identify endocardial borders accurately. Therefore, a robust and accurate automated method for segmentation is highly desirable to avoid from human mistakes and make it easier, faster and more accurate, particularly for the less-experienced echo-cardiologist. In this thesis at first for denoising the echocardiography images, a new method with use of Intensity Variation Time Curves and applying Wavelet function on them is proposed. In this case, structure of images is preserved and the bluring effect is disappear. In the sequel an automatic method for segmentation of the left ventricle border in three dimensional (3-D) echocardiography with B-spline Explicit Active Surface is proposed, that is new formulation of active contours based on explicit function. With applying proposed denoising method in data before segmentation the algorithm had best performance.
A challenging issue for echocardiographic image interpretation is the accurate analysis of small transient motions of myocardium and valves during real time visualization. A higher frame rate video may reduce this difficulty, and temporal super resolution (TSR) is useful for illustrating the fast-moving structures. In this thesis, a novel framework that optimizes TSR enhancement of echocardiographic images by utilizing temporal information and B-spline interpolation is introduced. The goal of this method is to increase the frame rate of echocardiographic videos, and therefore enable more accurate analyses of moving structures. Due to the MSE 0.4382 for 2D data and 0.1893 for 3D volumes this method had best performance. This method can be useful for cardiologist in low frame rates in 3D echocardiography.
