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  • 1.
    Grishenkov, Dmitry
    KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, MWL Ultrasound. KTH, School of Technology and Health (STH), Medical Engineering.
    Diagnostic Power of Different Tissue Doppler Parameters during Ultrasound Cardio-Vascular Investigation2007Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The department of Medical Technology, where I have done Master thesis project, develops and researches new method and technique within areas where ultrasound can be used to obtain the image of anatomical structure, functional capabilities and to suggest required treatment.

    Nowadays cardio-vascular diseases, such as infarct, atherosclerosis and ischemic syndrome, are one of the most widespread diseases in the world that’s why timely detection, identification and treatment are so important.

    The Master of Science qualification report consists 3 major parts: Medico-biological part, Design and Research parts.

    In Medico-biological part has been analyzed anatomical and physiological structure of the heart, current status of echocardiography with comparing with other techniques, summary of ultrasound methods with list of parameters that can be achieved is presented.

    In Design part has been developed new graphical modality based on Delta-V pump model using vector based statistical analysis for identification patients with ischemia. Software algorithm for automatically determine characteristic points for state diagram written in MatLab has been developed and implemented.

    In Research part in the first task using commercially available software based on Principal Component Analysis collected data from the hospital patients has been studied, results proved hypothesis concerning time variables importance; in the second task graphical module has been examined using collected data from the hospital patients both normal and with different cardio-vascular disease, and the results show good detection power of the algorithm.

    At the end of the project presentation has been done and report has been published.

    This project has been done in collaboration with the biggest medical institute in Sweden – Karolinska Institute - and results will be used in medical practice in Karolinska University Hospital in Huddinge and for future scientific needs.

     

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