Multidimensional Echocardiography Image Segmentation using Deep Learning Convolutional Neural Network

Hasan Imaduddin, Riyanto Sigit, Anhar Risnumawan

2021

Abstract

One of the most dangerous diseases that threaten human life is heart disease. One way to analyze heart disease is by doing echocardiography. Echocardiographic test results can indicate whether the patient’s heart is normal or not by identifying the area of the heart cavity. Therefore, many studies have emerged to analyze the heart. Therefore I am motivated to develop a system by inputting four points of view of the heart, namely 2 parasternal views (long axis and short axis) and 2 apical views (two chambers and four chambers) with the aim of this study being able to segment the heart cavity area. This research is part of a large project that aims to analyze the condition of the heart with 4 input points of view of the heart and the project is divided into several sections. For this research, it focuses on the process of echocardiographic image segmentation to obtain images of the heart cavity with 4 input points of view of the heart using the Deep Learning method by using the VGG-16 and RESNET-18 architecture. The training process is done using 30 epochs with 50 iterations per epoch and 1 batch size so that the total iteration is 7500 iterations. It can be seen that during the training process, the percentage accuracy is already high, reaching 95% -99%. On the VGG-16 architecture, it has an average accuracy in each viewpoint of around 83% -93%. The architecture of RESNET-18 has an average accuracy in every point of view which is around 76% -92%.

Paper Citation

in Harvard Style

Imaduddin H., Sigit R. and Risnumawan A. (2021). Multidimensional Echocardiography Image Segmentation using Deep Learning Convolutional Neural Network. In Proceedings of the 4th International Conference on Applied Science and Technology on Engineering Science - Volume 1: iCAST-ES, ISBN 978-989-758-615-6, pages 1250-1254. DOI: 10.5220/0010963200003260

in Bibtex Style

@conference{icast-es21,
author={Hasan Imaduddin and Riyanto Sigit and Anhar Risnumawan},
title={Multidimensional Echocardiography Image Segmentation using Deep Learning Convolutional Neural Network},
booktitle={Proceedings of the 4th International Conference on Applied Science and Technology on Engineering Science - Volume 1: iCAST-ES,},
year={2021},
pages={1250-1254},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010963200003260},
isbn={978-989-758-615-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Applied Science and Technology on Engineering Science - Volume 1: iCAST-ES,
TI - Multidimensional Echocardiography Image Segmentation using Deep Learning Convolutional Neural Network
SN - 978-989-758-615-6
AU - Imaduddin H.
AU - Sigit R.
AU - Risnumawan A.
PY - 2021
SP - 1250
EP - 1254
DO - 10.5220/0010963200003260