Abstract
4D flow Magnetic Resonance Imaging (4D flow MRI) provides information that improves the estimation of hemodynamic characteristics of the aorta and allows further flow analysis. However, reliable segmentation of the aorta, required as a preliminary step, is still an open problem due to the low image quality. Thus, an automatic segmentation tool could encourage the use of 4D flow MRI in clinical practice for diagnostic and prognostic decision-making. In this paper, we propose a fully automatic multi-atlas-based method to segment the aorta using the systolic phase of 4D flow MRI. The Dice similarity coefficient and Hausdorff distance were used to quantify the performance. In addition, a statistical significance test between the maximum diameters obtained with the manual and automatic segmentations was conducted to determine the reliability of the automatic segmentations. The results show that our method could be a first reliable step towards automatic segmentation of the aorta in all phases of 4D flow MRI.
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Marin-Castrillon, D.M. et al. (2022). Multi-atlas Segmentation of the Aorta from 4D Flow MRI: Comparison of Several Fusion Strategies. In: Puyol Antón, E., et al. Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge. STACOM 2021. Lecture Notes in Computer Science(), vol 13131. Springer, Cham. https://doi.org/10.1007/978-3-030-93722-5_1
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DOI: https://doi.org/10.1007/978-3-030-93722-5_1
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