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Research Article · Open access · Published 20 December 2014

CAVITY SEGMENTATION AND STROKE VOLUME MEASUREMENT METHODS FROM ECHOCARDIOGRAPHIC IMAGES: REVIEW

Anas A. Abboud1, Rahmita Wirza Rahmat1, Suhaini Bin Kadiman1, Mohd Zamrin Bin Dimon2, Lili Nurliyana1, M. Iqbal Saripan1 & Hasan H. Khaleel1

Journal of Computer Science, Volume 10, Issue 11, pp. 2220–2231 · doi.org/10.3844/jcssp.2014.2220.2231

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Abstract

The complexity and criticality of heart disease diagnosis and treatment have frequently attracted the attention of researchers to develop approaches that can handle accurate clinical assessments. One of these complexities is measuring the Right Ventricle stroke volume. Therefore, different cardiac imaging techniques have been developed to help specialists in their regular clinical work and in the operating theatre to assist in the diagnosis, monitoring of the treatment and to ensure the success of a cardiac intervention as far as possible. Echocardiography is one of the cardiac imaging techniques and is considered as the most effective imaging technique as it is minimally invasive, quick and the cheapest method. Many studies have been conducted on Right Ventricle assessment from echocariographic images. This review is aimed at presenting the previous technical elements and algorithms used to measure the ventricle stroke volume from echocardiographic images. The review focuses on the five technical approaches that have been used, which are pre-processing, End-Distally (ED) and End-Systolic (ES) frame detection, cavity segmentation, the stoke volume measurement and 3D reconstruction. Finally, a summary will conclude this study.

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Abboud, A. A., Rahmat, R. W., Kadiman, S. B., Dimon, M. Z. B., Nurliyana, L., Saripan, M. I. & Khaleel, H. H. (2014). CAVITY SEGMENTATION AND STROKE VOLUME MEASUREMENT METHODS FROM ECHOCARDIOGRAPHIC IMAGES: REVIEW. Journal of Computer Science, 10(11), 2220–2231. https://doi.org/10.3844/jcssp.2014.2220.2231

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CAVITY SEGMENTATION AND STROKE VOLUME MEASUREMENT METHODS FROM ECHOCARDIOGRAPHIC IMAGES: REVIEWJournal of Computer Science · Volume 10, Issue 11 · pp. 2220–2231 · CC BY 3.0Download