BedBasedEcho

Bachelor thesis (2020)

Authors

J. Haas Electrical Engineering, Mathematics and Computer Science
R.F. Klazinga Electrical Engineering, Mathematics and Computer Science
N. van Stijn Electrical Engineering, Mathematics and Computer Science
J. Teunissen Electrical Engineering, Mathematics and Computer Science
Y. Zhang Electrical Engineering, Mathematics and Computer Science

Contributors

M. Loog Pattern Recognition and Bioinformatics - EEMCS (mentor)
Eelko Ronner (mentor)
O.W. Visser Computer Science & Engineering-Teaching Team - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2020 Joey Haas, Rembrandt Klazinga, Nick van Stijn, Jasper Teunissen, Peter Zhang
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Published Date

15-07-2020

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

The core challenge of the BedBasedEcho BEP project is to create an algorithm to find the heart, and apply it on a robotic echocardiography solution. The team has found multiple complex solutions that are related to this problem, and has extracted useful information from these solutions to apply to this problem. However, some of these complex solutions were too complex, causing the team to run out of physical resources, or to have the solution fail entirely. By taking a step back, and simplifying the solution, the team has managed to create a system that performs marginally better than the complex solutions. The designed product consists of three major components: the data gathering, the learning, and the deployment. When used in this order, the result is an algorithm that can predict which way it should move to gain the optimal view of the heart. The algorithm will be used as a component in a larger automated echocardiography system. Ultimately, the algorithm showed promise by autonomously finding a good view of the heart.

Files

BBE_FINAL.pdf
(pdf | 0.887 Mb)