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2017 | OriginalPaper | Chapter

Patient-Specific Cardiac Computational Modeling Based on Left Ventricle Segmentation from Magnetic Resonance Images

Authors : Anupama Bhan, Disha Bathla, Ayush Goyal

Published in: Proceedings of the International Conference on Data Engineering and Communication Technology

Publisher: Springer Singapore

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Abstract

This paper presents three-dimensional computational modeling of the heart’s left ventricle extracted and segmented from cardiac MRI. This work basically deals with the fusion of segmented left ventricle, which is segmented using region growing method, with the generic deformable template. The multi-frame cardiac MRI image data of heart patients is taken into account. The region-based segmentation is performed in ITK-SNAP. The left ventricle is segmented in all slices in multi-frame MRI data of the whole cardiac cycle for each patient. Various parameters like myocardial muscle thickness can be calculated, which are useful for assessing cardiac function and health of a patient’s heart by medical practitioners. With the left ventricle cavity and myocardium segmented, measurement of the average distance from the endocardium to the epicardium can be used to measure myocardial muscle thickness.

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Metadata
Title
Patient-Specific Cardiac Computational Modeling Based on Left Ventricle Segmentation from Magnetic Resonance Images
Authors
Anupama Bhan
Disha Bathla
Ayush Goyal
Copyright Year
2017
Publisher
Springer Singapore
Book
Proceedings of the International Conference on Data Engineering and Communication Technology

Print ISBN: 978-981-10-1677-6

Electronic ISBN: 978-981-10-1678-3

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-981-10-1678-3_17

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