CAVITY SEGMENTATION AND STROKE VOLUME MEASUREMENT METHODS FROM ECHOCARDIOGRAPHIC IMAGES: REVIEW
- 1 , Malaysia
- 2 Universiti Teknologi MARA(UiTM), Malaysia
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.
DOI: https://doi.org/10.3844/jcssp.2014.2220.2231
Copyright: © 2014 Anas A. Abboud, Rahmita Wirza Rahmat, Suhaini Bin Kadiman, Mohd Zamrin Bin Dimon, Lili Nurliyana, M. Iqbal Saripan and Hasan H. Khaleel. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Echocardiography Image
- Stroke Volume
- Right Ventricle (RV)
- Left Ventricle (LV)
- End-Diastolic (ED) and End-Systolic (ES)
- Three Dimensional Echocardiography (3DE)
- Pre-processing
- Segmentation
- 3D illustration
- Cloud Point Orientation