Correlation based 3-D segmentation of the left ventricle in pediatric echocardiographic images using radio-frequency data
Publication year
2011Source
Ultrasound in Medicine and Biology, 37, 9, (2011), pp. 1409-20ISSN
Publication type
Article / Letter to editor
![https://hdl.handle.net/2066/95767](https://cdn.statically.io/img/repository.ubn.ru.nl/themes/Mirage2//images/copy.png)
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Organization
Radiology
Paediatrics - OUD tm 2017
Journal title
Ultrasound in Medicine and Biology
Volume
vol. 37
Issue
iss. 9
Page start
p. 1409
Page end
p. 20
Subject
IGMD 1: Functional imaging; IGMD 1: Functional imaging NCEBP 14: Cardiovascular diseases; ONCOL 5: Aetiology, screening and detection; Medical Imaging - Radboud University Medical CenterAbstract
Clinical diagnosis of heart disease might be substantially supported by automated segmentation of the endocardial surface in three-dimensional (3-D) echographic images. Because of the poor echogenicity contrast between blood and myocardial tissue in some regions and the inherent speckle noise, automated analysis of these images is challenging. A priori knowledge on the shape of the heart cannot always be relied on, e.g., in children with congenital heart disease, segmentation should be based on the echo features solely. The objective of this study was to investigate the merit of using temporal cross-correlation of radio-frequency (RF) data for automated segmentation of 3-D echocardiographic images. Maximum temporal cross-correlation (MCC) values were determined locally from the RF-data using an iterative 3-D technique. MCC values as well as a combination of MCC values and adaptive filtered, demodulated RF-data were used as an additional, external force in a deformable model approach to segment the endocardial surface and were tested against manually segmented surfaces. Results on 3-D full volume images (Philips, iE33) of 10 healthy children demonstrate that MCC values derived from the RF signal yield a useful parameter to distinguish between blood and myocardium in regions with low echogenicity contrast and incorporation of MCC improves the segmentation results significantly. Further investigation of the MCC over the whole cardiac cycle is required to exploit the full benefit of it for automated segmentation.
This item appears in the following Collection(s)
- Academic publications [241901]
- Electronic publications [127360]
- Faculty of Medical Sciences [91954]
- Open Access publications [102119]
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