Informatica

This study aims to evaluate patients with limited state of changes in coronary arteries detected by coronary angiography, the dynamics of these changes over the two years, identify the relevant diagnostic criteria, and assess the efficacy of applied treatment by using speckle tracking echocardiography. Peak radial and circumferential strain and SR (systolic, early, and late diastolic strains) were measured based on the short-axis view; peak longitudinal strain and SR were measured from the apical side of four- two- and three-chamber views. Radial, longitudinal (GLS), circumferential global and regional strains were calculated as an average of measurements. All patients $(n-146)$ were assigned to normal (control) and CAD groups according to cardiac angiography results. 128 of them were evaluated repeatedly after two years. Depending on angiography findings, LAD (85.83%) stenosis predominate, when subsequently fewer instances of RCA (52.5%) or LCX (40.83%) were observed. Most (about 80%) of the patients had one or two-vessel disease and only 20% had systemic all three-vessel disease. Analysis of STE data in groups during a two-year study period showed statistically reliable differences associated with a particular coronary artery. In the control group: RCA – myocardial circumferential strain $(p-0.037)$; LAD – no changes; LCX – early $(p-0.013)$ and late diastolic longitudinal $(p-0.033)$ strains. Subsequently, in the CAD group: RCA – diastolic circumferential strain rate $(p-0.007)$; LAD – myocardial longitudinal strain $(p-0.006)$, systolic longitudinal $(p-0.038)$ and circumferential strain $(p-0.012)$ rates, early diastolic circumferential $(p-0.008)$ and late diastolic longitudinal $(p-0.037)$ strain rates; LCX – myocardial longitudinal $(p-0.049)$ strain. Between groups, we detected significant changes in such circumferential strain rates, respectively: RCA – systolic $(p=0.037)$, early diastolic $(p=0.019)$, and late diastolic $(p=0.024)$ strain rates; LAD – no changes; LCX – early diastolic longitudinal strain $(p-0.004)$. The clinical condition of our patients over the two years has improved both in control and CAD groups, according to GLS. We hold the opinion that microvascular angina (MVA) may be responsible for such an improvement because the main diagnostic criteria and common treatment with ACE inhibitors, statins, β-blockers, antithrombotic, and nitrates was typical and effective for MVA treatment.

The paper considers application of stochastic optimization to system of automatic recognition of ischemic stroke area on computed tomography (CT) images. The algorithm of recognition depends on five inputs that influence the results of automatic detection. The quality of recognition is measured by size of conjunction of ethalone image and the image calculated by the program of automatic detection. The method of Simultaneous Perturbation Stohastic Approximation algorithm with the Metropolis rule has been applied to the optimization of the quality of image recognition. The Monte-Carlo simulation experiment was performed in order to evaluate the properties of developed algorithm.

The paper describes a new method to segment ischemic stroke region on computed tomography (CT) images by utilizing joint features from mean, standard deviation, histogram, and gray level co‐occurrence matrix methods. Presented unsupervised segmentation technique shows ability to segment ischemic stroke region.

The aim of investigation was to seek new ways for the analysis of extremal problems. A method of visual analysis of a set of objective function values is proposed. It allows us to find a direction where the variation of function is maximal. The method ensures a high quality of analysis when the number of used values of the objective function is small, and a possibility of identifying a specific character of the objective function. The results of analysis are used in search of a new coordinate system of the extremal problem and in a graphical representation of the observed data. The analysis will lead us to a better optimization strategy.

The problem is to discover knowledge in the correlation matrix of parameters (variables) about their groups. Results that deal with deterministic approaches of parameter clustering on the basis of their correlation matrix are reviewed and extended. The conclusions on both theoretical and experimental investigations of various deterministic strategies in solving the problem of extremal parameter grouping are presented. The possibility of finding the optimal number of clusters is considered. The transformation of a general clustering problem into the clustering on the sphere and the relation between clustering of parameters on the basis of their correlation matrix and clustering of vectors (objects, cases) of an n-dimensional unit sphere are analysed.