2D/3D fetal cardiac dataset segmentation using a deformable model

Dindoyal, Irving, Lambrou, Tryphon, Deng, Jing and Todd-Pokropek, Andrew (2011) 2D/3D fetal cardiac dataset segmentation using a deformable model. Medical Physics, 38 (7). p. 4338. ISSN 0094-2405

Full content URL: http://dx.doi.org/10.1118/1.3592638

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Item Type:Article
Item Status:Live Archive


Purpose: To segment the fetal heart in order to facilitate the 3D assessment of the cardiac function and structure.

Methods: Ultrasound acquisition typically results in drop-out artifacts of the chamber walls. The authors outline a level set deformable model to automatically delineate the small fetal cardiac chambers. The level set is penalized from growing into an adjacent cardiac compartment using a novel collision detection term. The region based model allows simultaneous segmentation of all four cardiac chambers from a user defined seed point placed in each chamber.

Results: The segmented boundaries are automatically penalized from intersecting at walls with signal dropout. Root mean square errors of the perpendicular distances between the algorithm's delineation and manual tracings are within 2 mm which is less than 10% of the length of a typical fetal heart. The ejection fractions were determined from the 3D datasets. We validate the algorithm using a physical phantom and obtain volumes that are comparable to those from physically determined means. The algorithm segments volumes with an error of within 13% as determined using a physical phantom.

Conclusions: Our original work in fetal cardiac segmentation compares automatic and manual tracings to a physical phantom and also measures inter observer variation.

Keywords:segmentation; fetal; fetus; heart; cardiac
Subjects:F Physical Sciences > F350 Medical Physics
G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
ID Code:7120
Deposited On:14 Dec 2012 10:35

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