Segmentation Methods of Echocardiography Images for Left Ventricle Boundary Detection
Samaneh Mazaheri1, Rahmita Wirza1, Puteri Suhaiza Sulaiman1, Mohd Zamrin Dimon2, Fatima Khalid1 & Rohollah Moosavi Tayebi1 Show affiliations
- UPM, Malaysia
- UiTM, Malaysia
Journal of Computer Science, Volume 11, Issue 9, pp. 957–970 · doi.org/10.3844/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.
Licence and reuse
Open access. This article is licensed under a Creative Commons Attribution 3.0 Licence (CC BY 3.0), as printed on the article, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors and the source. No permission is needed.
How to reuse this articleResponses (0)
About this article
Mazaheri, S., Wirza, R., Sulaiman, P. S., Dimon, M. Z., Khalid, F. & Tayebi, R. M. (2015). Segmentation Methods of Echocardiography Images for Left Ventricle Boundary Detection. Journal of Computer Science, 11(9), 957–970. https://doi.org/10.3844/jcssp.2015.957.970
- Licence
- CC BY 3.0
- Issue
- Volume 11, Issue 9
- Policies
- Editorial independenceUse of generative AIData availabilityAppeals and complaints
- Version
- Version of record
