ندا گرجي كندي

Heart disease has been the most reason for death among people all over the world. Considering the function of left ventricle which plays a significant role in blood circulation and transmission of blood to every single organ of the body can help with the diagnosis of heart diseases. It is obvious that observing the function and heart condition is truly helpful for prevention of heart problems. Identification and assessment of left ventricular (LV) regional and global wall motion abnormalities on echocardiography images has fundamental clinical importance for various cardiovascular disease assessments especially in ischemia. In clinical practice, this eva‎luation is still performed manually or visually which is tedious and time consuming and highly dependent on training and experience of the echocardiographers and therefore suffers from significant interobserver and intraobserver variability. Consequently, a robust and accurate automated method is highly desirable to obtain more objective and quantitative diagnosis, particularly for the less experienced echocardiographers. Therefore, providing automatic image processing methods based on entropy algorithm to identify and quantitatively, accurately and quickly eva‎luate these anomalies is the main focus of this research. In this study, a group of experiments were conducted to check the efficiency of this algorithm. A data set containing 7 two-dimensional echocardiographic images from the 4-chamber view of the heart of 3 healthy and 4 sick people, whose number of frames is between 100 and 250 and each data contains 2 to 6 cardiac cycles, which was prepared by our own research group, was applied. From the echocardiographic sequence, the first frame is determined as a reference to determine manually the region of interest (ROI) on it, then it is applied to all frames and is considered as a Pre-Processing step, and in the processing step the function entropy is obtained on all frames and the result is displayed as a graph, and this process is continuously performed on all sequences of four-hole images of the data set. And this allows the expert to compare easily the results with each other.

تصاوير اكوكارديوگرافي , بطن چپ , آنتروپي , بيماري‌هاي قلبي عروقي

Echocardiography images , Entropy , Left ventricular , Cardiovascular diseases

Neda gorji kandi

Hamid behnam