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Pattern Recognition and Image Analysis
Erschienen in: Pattern Recognition and Image Analysis 3/2020

01.07.2020 | APPLIED PROBLEMS

An Integrated Segmentation Techniques for Myocardial Ischemia

verfasst von: R. Merjulah, J. Chandra

Erschienen in: Pattern Recognition and Image Analysis | Ausgabe 3/2020

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Abstract

Myocardial Ischemia segmentation is a challenging task for basic and translational research on cardiovascular, as it provides ultimately “realistic” in heart muscle model. The main objective of the research work is to find an efficient segmentation technique for the myocardial ischemia based on the myocardial infarcted MRI data set for the accurate classification of scar volume. The paper will give an insight about the segmentation technique based on myocardial ischemia and discusses essential cellular components. The paper provides an integrated approach which comprises of fuzzy c-means and morphological operations along with median filtering enhancement technique help in detecting the myocardial ischemia. The developed model is tested with 2D and 3D enhanced myocardial ischemia MRI and also with normal heart. The purpose of segmentation in myocardial ischemia is to identify the scar region in the heart. The integrated model is evaluated based on statistical measures and validated based on manual segmentation done by clinical expert. The scar classification is done based on the myocardial ischemia segmentation which leads to better prediction of arrhythmia in heart patient. The integrated model is considered as one of the best model for segmenting myocardial ischemia.
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Metadaten
Titel
An Integrated Segmentation Techniques for Myocardial Ischemia
verfasst von
R. Merjulah
J. Chandra
Publikationsdatum
01.07.2020
Verlag
Pleiades Publishing
Erschienen in
Pattern Recognition and Image Analysis / Ausgabe 3/2020
Print ISSN: 1054-6618
Elektronische ISSN: 1555-6212
DOI
https://doi.org/10.1134/S1054661820030190

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