@article {10.3844/jcssp.2015.957.970,
article_type = {journal},
title = {Segmentation Methods of Echocardiography Images for Left Ventricle Boundary Detection},
author = {Mazaheri, Samaneh and Wirza, Rahmita and Sulaiman, Puteri Suhaiza and Dimon, Mohd Zamrin and Khalid, Fatima and Tayebi, Rohollah Moosavi},
volume = {11},
number = {9},
year = {2015},
month = {Dec},
pages = {957-970},
doi = {10.3844/jcssp.2015.957.970},
url = {https://thescipub.com/abstract/jcssp.2015.957.970},
abstract = {Due to acoustic interferences and artifacts which are inherent in echocardiography images, automatic segmentation of anatomical structures in cardiac ultrasound images is a real challenge. This paper surveys state-of-the-art researches on echocardiography data segmentation methods, concentrating on methods techniques developed for clinical data. We present a classification of methodologies for echocardiography image segmentation. By choosing ten recent papers which have proposed innovative ideas that they proved certain clinical advantages or potential especial role to the echocardiography segmentation task. The contribution of the paper would be serving as a tutorial of the field for both clinicians and technologists, providing large number of segmentation techniques in a comprehensive and systematic manner and critically review recent approaches in terms of their performance and degree of clinical evaluation with respect to the final goal of cardiac functional analysis.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}