Abstract
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.
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.
Original language | English |
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Pages (from-to) | 4338-4349 |
Number of pages | 12 |
Journal | Medical Physics |
Volume | 38 |
Issue number | 7 |
DOIs | |
Publication status | Published - Jul 2011 |
Bibliographical note
cited By 5ACKNOWLEDGMENTS
This work was supported by EPSRC (GR/N14248/01) and MRC (D2025/31) under the Interdisciplinary Research Consortium scheme—“From Medical Images and Signals to Clinical Information” (MIAS IRC). Dr. Jing Deng is supported by MRC (G108/516).