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2017 | OriginalPaper | Buchkapitel

Quantitative Assessment of Heart Function: A Hybrid Mechanism for Left Ventricle Segmentation from Cine MRI Sequences

verfasst von : Muhammad Sohaib, Jong-Myon Kim

Erschienen in: Artificial Life and Computational Intelligence

Verlag: Springer International Publishing

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Abstract

In this paper, we propose a hybrid approach for segmenting the left ventricle out of magnetic resonance sequences and apply results of the segmentation for heart quantification. The hybrid approach uses a thresholding-based region growing algorithm coupled with gradient vector flow (GVF). Results of the segmentation steps were used for the quantification process and yielded values of 175.4 ± 51.52 (ml), 66 ± 38.97 (ml), and 61.60 ± 12.79 (%) for end diastolic volume (EDV), end systolic volume (ESV), and ejection fraction (EF), respectively.

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Titel: Quantitative Assessment of Heart Function: A Hybrid Mechanism for Left Ventricle Segmentation from Cine MRI Sequences
verfasst von: Muhammad Sohaib
Jong-Myon Kim
Verlag: Springer International Publishing
Buch: Artificial Life and Computational Intelligence
Print ISBN: 978-3-319-51690-5

Electronic ISBN: 978-3-319-51691-2

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-51691-2_15

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