Three-dimensional speckle-tracking echocardiography can be an effective noninvasive method for assessing 3D LV twist. Age-related differences in the 3D LV twist may be the result of the age-related changes in the endocardial myofibers.
Ischemic heart disease is a leading cause of death in the modern world. Coronary obstruction is the basis for ischemic heart disease and leads to decreased cardiac supply and decreased contractility of the myocardium. Recently, high quality 4D computed tomography (CT) has become available for cardiac imaging and provides the clinician with high quality anatomical images. In this article, a new method is proposed to detect 3D motion and strain from 4D cardiac CT images by constraining intensity constancy, myocardial volume changes and motion smoothness assumptions. The proposed method is validated by using manual tracking of the cardiac CT landmarks. The average error for the manual tracking, by an expert, was 2.9 ± 0.9 mm. As an additional validation, the cardiac CT strain values were compared to the cardiac tagged magnetic resonance imaging (MRI) and 2D B-mode echocardiography strain values of the same patients. The correlation ratio was significantly high for CT and tagged MRI radial strain values (r = 0.76, 95% confidence interval, P < 0.001). The correlation ratio was meaningful for CT and echocardiography radial strain values as well (r = 0.67, 95% confidence interval, P < 0.001). The correlation ratio for CT and tagged MRI circumferential strain values was acceptable (r = 0.73, 95% confidence interval, P < 0.001), while the correlation ratio for CT and echocardiography circumferential strain values was good as well (r = 0.61, 95% confidence interval, P < 0.001). In general, motion and strain values computed from cardiac CT images agree with motion and strain values computed from tagged MRI and echocardiography images.
Since myocardial motion is directly related to cardiac vascular supply, it can be helpful in diagnosing the heart abnormalities. The most comprehensive and available imaging study of the cardiac function is B-Mode echocardiography. However diagnostic systems are expert dependent and motion is not clear in the B-mode echocardiography images and therefore many efforts are pointed toward proposing new methods to measure the motion accurately. So far there have been many methods for myocardial motion estimation such as affine registration, elastic registration or optical flow but each method suffers from lack of accuracy. To increase the accuracy of motion detection techniques, we propose a new algorithm based on a variational technique to combine the efficiencies of optical flow methods and affine registration in combination with multi-resolution spatiotemporal Spline moments. The evaluation was performed on simulated, synthetic and real data. A comparison between the proposed method and several other methods shows its better performance to measure the motion more accurately in the presence of shear, rotation and noise. The proposed method achieved rotational error of 2.6 degrees per frame and amplitude error of 3.7 percent per frame. These results demonstrate a better efficiency with respect to other B-Mode echocardiography motion estimation techniques such as Lucas-Kanade, Horn-Schunck and spatiotemporal affine technique.
An electrocardiogram (ECG) feature extraction and classification system has been developed and evaluated using Quartus II 7.1 belong to Altera Ltd. In wavelet domain QRS complexes were detected and each complex was used to locate the peaks of the individual waves. Then, fuzzy classifier block used these features to classify ECG beats. Three types of arrhythmias and abnormalities were detected using the procedure. The completed algorithm was embedded into Field Programmable Gate Array (FPGA). The completed prototype was tested through software-generated signals, in which test scenarios covering several kinds of ECG signals on MIT-BIH Database. For the purpose of feeding signals into the FPGA, a software was designed to read signal files and import them to the LPT port of computer that was connected to FPGA. From the results, it was achieved that the proposed prototype could do real time monitoring of ECG signal for arrhythmia detection. We also implemented algorithm in a sequential structure device like AVR microcontroller with 16 MHZ clock for the same purpose. External clock of FPGA is 50 MHZ and by utilizing of Phase Lock Loop (PLL) component inside device, it was possible to increase the clock up to 1.2 GHZ in internal blocks. Final results compare speed and cost of resource usage in both devices. It shows that in cost of more resource usage, FPGA provides higher speed of computation; because FPGA makes the algorithm able to compute most parts in parallel manner.
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