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  1. Department of Circulation and Medical Imaging Department of Circulation and Medical Imaging
  2. Department of Circulation and Medical Imaging
  3. Department of Circulation and Medical Imaging

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Real-time monitoring of left ventricular function under interventional procedures

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  • Department of Circulation and Medical Imaging
    • Department of Circulation and Medical Imaging
    • Department of Circulation and Medical Imaging
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Master's thesis and projects

Master's thesis and projects

– Ultrasound technology

The Department of circulation and medical imaging offers projects and master's thesis topics for technology students of most of the different technical study programmes at NTNU. There is a seperate page for the supplementary specialisation courses.

List of topics

Topics for thesis and projects are given below. Most of the topics can be adjusted to the students qualifications and wishes.

Don't hesitate to take contact with the corresponding supervisor - we're looking forward to a discussion with you!

Ressurspublisering

null Real-time monitoring of left ventricular function under interventional procedures

Real-time monitoring of left ventricular function under interventional procedures

Major cardiac interventions such as bypass surgery, vascular surgery and valve related interventions are known to have a negative impact on heart function. As of today patient monitoring during the intervention is performed by a combination of vital signs monitoring (i.e. blood pressure, heart rate, blood oxygen saturation) and clinical observation by the anesthesiologist. Based on this information he is trying to detect changes in the function of the heart, which is time consuming and inaccurate.

The aim of this project is to develop an algorithm capable of detecting changes in the function of the heart and specifically of the left ventricle, based on blood pressure, ECG measurements as well as echocardiographic parameters obtained during continuous automated monitoring, which are proven to correlate well with the function of the heart.

Objectives:

  • Extend existing data transfer and logging tools by adding support for the computation and tracking of parameters related to left ventricular function
  • Identify which parameters are best suited for identifying early signs of changes in left ventricular function
  • Develop machine learning based tools for automatic detection of functional changes
  • Validate the methods on recorded patient data

Skills:

  • Knowledge of Matlab or C++ programming

Contact:

  • Gabriel Kiss
  • Svend Aakhus
  • Hans Torp

How to write ...

How to write ...

  • a good abstract
  • a good introduction

person-portlet

Contact

  • Lasse Løvstakken

    Lasse Løvstakken Professor

    lasse.lovstakken@ntnu.no Department of Circulation and Medical Imaging

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