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Segmentation of RT3D Ultrasound with Implicit Deformable Models Without Gradients

Angelini, Elsa D.; Holmes, Jeffrey W.; Laine, Andrew F.; Homma, Shunichi

This paper presents the implementation and validation of a new 3D deformable model method, based on the Mumford-Shah functional for segmentation of three-dimensional real-time ultrasound. An experiment on 10 patients with primary hypertension was carried out to compare three segmentation methods for quantification of right and left ventricular ejection fraction: (1) manual tracing by an expert cardiologist, (2) 2D parametric deformable model, and (3) 3D implicit deformable model implemented with a level set framework. Deformable model segmentations were performed on denoised data using a (3D+Time) brushlet expansion. The clinical study showed superior performance of the deformable model in assessing ejection fraction when compared to MRI measures. It also showed that the three-dimensional deformable model improved EF measures, which is explained by a more accurate segmentation of small and convoluted ventricular shapes when integrating the third spatial dimension.


More About This Work

Academic Units
Biomedical Engineering
Published Here
August 13, 2010


ISPA 2003: Proceedings of the 3rd International Symposium on Image and Signal Processing and Analysis: Rome, Italy, September 18-20, 2003, vol. 2 (Piscataway, N.J.: IEEE, 2004), pp. 711-716.

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