Artem M. Yatchenko
Moscow State University
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Featured researches published by Artem M. Yatchenko.
visual communications and image processing | 2011
Artem M. Yatchenko; Andrey S. Krylov; Andrey Gavrilov; Ivan V. Arkhipov
An unwrapping method for Doppler ultrasound color flow medical images has been developed. It is based on a image digitizing procedure to construct the areas graph. The minimization unwrapping procedure of the velocity field is based on the graph-cut method.
Neurocomputing | 2014
Artem M. Yatchenko; Andrey S. Krylov; Valeriy A. Sandrikov; Tatyana Yu. Kulagina
An antialiasing method for the captured phase data obtained by color Doppler flow mapping has been proposed. It is based on minimization of the regularization functional with stabilizing terms taking into account features of the ultrasound investigation. The proposed method allows us to solve the problem even in the case of existing areas with unknown data and turbulent flow regions. Test results for the left ventricle color Doppler flow mapping and comparison with the existing unwrapping methods showed effectiveness of the algorithm.
sino foreign interchange conference on intelligent science and intelligent data engineering | 2012
Artem M. Yatchenko; Andrey S. Krylov
Iterative regularization method to process captured data by color Doppler flow mapping has been proposed. It takes into account features of the ultrasound investigation and allows to solve the problem even in the case of noisy data and in the case of existing areas with unknown flow values. The influence of the values of regularization parameters on the obtained solution was analyzed. Test results for the left ventricle color Doppler flow mapping investigation showed effectiveness of the algorithm.
international conference on functional imaging and modeling of heart | 2015
Artem M. Yatchenko; Andrey S. Krylov
Ultrasonic color Doppler flow image unwrapping algorithm that uses cross-frame connection is proposed and compared with other unwrapping methods. An original complex phase preliminary filtration is used to suppress a false-aliasing artifact and to improve the results. Flow variances are used as weight coefficients in the minimization energy function. For the comparison a test data series is constructed. It uses an anatomic 3D left ventricle region model for the simulation of the blood flow. Experiments show that cross-frame weights significantly improve the quality of unwrapping.
Russian Journal of Cardiology | 2014
V. A. Sandrikov; T. Yu. Kulagina; Andrey S. Krylov; Artem M. Yatchenko
Aim. To evaluate the treatment results and to estimate the early predictors for myocardial dysfunction in patients with DCMP. Material and methods. Totally 69 patients with DCMP (median age 42±14) were investigated before and after operation. Patients were divided into 3 groups: 1st — 69 patients before surgical treatment; 2nd — 41 patients those who were examined in 9-12 months after operation; 3rd — patients being monitored for more than 24 months after operation. The control consisted of 110 volunteers with the menian age 37±8 y.o. To all patients the echocardiography was applied using expert class Vivid E9 (GE, USA) machine with multifrequency sensor 3,5-5,0 MHz. To visualize flows in the left ventricle the flow velocity was registered in the areas of fiber ring, middle and apical areas. Results. With the LV function disturbing in DCMP patients the rise of pre- and postload causes significant changes in myocardial functioning. The direction of blood flow in the LV significantly changes with hypertrophy of myocardium and papillary muscles, valve dysfunction and other disorders. We had concluded that in DCMP, at the same time with high EDV and ESV there is incessance of blood flow which determines heart work by continuous blood motion, elasticity of magistral vessels and myocardium contraction. By echocardiography and computed tomography it was found that heart rotation is in order from the right to the left segments of basal area and then to descending and ascending segments of the heart apex. Conclusion. The velocity of myocardial shifts, of blood flows in the LV make possible to evaluate heart functioning in patients with heart failure and to estimate the effectiveness of surgical treatment in closer and further postoperational periods. Basing on the measurements of blood flows in heart chambers and on estimation of intraventricular pressure gradients (from the apex to basement) it is possible to analyse the functioning and the performance of valves in patients with DCMP. The appearance in LV of additional turbulent flows, the decrease of flow velocity during the cardiac contraction cycle in one or another part are responsible for the failure and can be regarded as early predictors of myocardial dysfunction.
Pattern Recognition and Image Analysis | 2013
Artem M. Yatchenko; Andrey S. Krylov; Andrey V. Nasonov
A no-reference method to detect and suppress ringing effect in MRI images is suggested. The ringing detection method is based on finding the area where ringing effect is likely to appear and calculating the ratio of average edge-normal and edge-tangential derivatives moduli in this area. The area consists of pixels with the certain distance to basic edges—sharp edges that are distant from other edges. The proposed ringing suppression method is based on the projection onto the set of images with bounded total variation with ringing level control.
Pattern Recognition and Image Analysis | 2012
Artem M. Yatchenko; Andrey S. Krylov; Andrey Gavrilov; I. V. Arkhipov
A three-dimensional dynamic reconstruction algorithm of the left ventricle of patient’s heart from ultrasonic echocardiography data is developed. The presented algorithm takes into account the longitudinal and transverse velocities of ventricle walls to determine the motion vectors of the ventricular walls. Two longitudinal ultrasonic sections (four-chamber position and two-chamber position) and two transverse ultrasonic sections (at a level of basal segments and at a level of papillary muscles) are used for the reconstruction.
Pattern Recognition and Image Analysis | 2011
Artem M. Yatchenko; Andrey S. Krylov; Andrey Gavrilov; Ivan V. Arkhipov
Dynamic heart model of the left ventricular border motion taking into account both longitudinal and transverse velocities of the border has been developed. It uses two longitudinal (4-chamber and 2-chamber apical long axis) and two ltransversal (papillary muscles and basal parasternal short axis) ultrasound views for the reconstruction.
Lecture Notes in Computer Science | 2013
Artem M. Yatchenko; Andrey S. Krylov
Computational Mathematics and Modeling | 2013
Artem M. Yatchenko; Andrey S. Krylov