Abstract
Assessment of the left atrial (LA) wall can provide valuable information for treatment of atrial fibrillation (AF) patients. In this work, we propose a fully automatic workflow to segment the atrial wall from contrast-enhanced CT angiography (CTA). The workflow consists of 3 steps: (1) global segmentation of LA by multi-atlas image registration approach, (2) selected enhancement of the atrial wall by nonlinear intensity transformation, (3) segmentation of the inner and outer boundary of atrial wall by level-set approach.
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Acknowledgement
The authors gratefully acknowledge the support from the Dutch Technology Foundation, with grant number OTP12899.
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Tao, Q., Shahzad, R., Berendsen, F.F., van der Geest, R.J. (2017). Automatic Left Atrial Wall Segmentation from Contrast-Enhanced CT Angiography Images. In: Mansi, T., McLeod, K., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. STACOM 2016. Lecture Notes in Computer Science(), vol 10124. Springer, Cham. https://doi.org/10.1007/978-3-319-52718-5_24
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DOI: https://doi.org/10.1007/978-3-319-52718-5_24
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