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Technical Program
Paper Detail
| Paper: | TP-P3.10 |
| Session: | Biomedical Image Segmentation and Quantitative Analysis |
| Time: | Tuesday, October 10, 14:20 - 17:00 |
| Presentation: |
Poster
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| Title: |
ULTRASOUND MYOCARDIAL TRACKING WITH SPECKLE REDUCING ANISOTROPIC DIFFUSION ASSISTED INITIALIZATION |
| Authors: |
Alla Aksel; University of Virginia | | | | | Robert L. Janiczek; University of Virginia | | | | | John A. Hossack; University of Virginia | | | | | Brent A. French; University of Virginia | | | | | Scott T. Acton; University of Virginia | | |
| Abstract: |
Cardiac parameters such as end-systolic volume, ejection fraction and myocardial mass are essential to the diagnosis and treatment of cardiovascular disease (CVD). Traditionally, these parameters are calculated based on manual myocardial segmentation by a trained technician. Fast, accurate, and automatic segmentation would provide researchers with an increased subject pool, an enhanced understanding of CVD, and may lead to the development of new therapies. In this paper we propose an automated algorithm for myocardial segmentation. This method utilizes speckle reducing anisotropic diffusion to assist the automated contour initialization. Speckle tracking segmentation (STS) is then applied throughout the cardiac cycle to track the myocardial borders. This approach, compared to standard active contour techniques, reduces the RMSE to ground truth by an order of magnitude. |
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