Abstract
We propose a semi-automatic endocardial border detection method for 3D+T cardiac ultrasound data based on pattern matching and dynamic programming, operating on 2D slices of the 3D+T data, for the estimation of LV volume, with minimal user interaction. It shows good correlations with MRI ED and ES volumes (r=0.938) and low interobserver variability (y=1.005x-16.7, r=0.943) over full-cycle volume estimations. It shows a high consistency in tracking the user-defined initial borders over space and time.
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van Stralen, M. et al. (2004). A Semi-automatic Endocardial Border Detection Method for 4D Ultrasound Data. In: Barillot, C., Haynor, D.R., Hellier, P. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. MICCAI 2004. Lecture Notes in Computer Science, vol 3216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30135-6_6
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DOI: https://doi.org/10.1007/978-3-540-30135-6_6
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