Abstract
Aortic stiffness is an important diagnostic and prognostic parameter for many diseases, and is estimated by measuring the Pulse Wave Velocity (PWV) from Cardiac Magnetic Resonance (CMR) images. However, this process requires combinations of multiple sequences, which makes the acquisition long and processing tedious. We propose a method for aorta segmentation and centerline extraction from para-sagittal Phase-Contrast (PC) CMR images. The method uses the order of appearance of the blood flow in PC images to track the aortic centerline from the seed start position to the seed end position of the aorta. The only required user interaction involves selection of 2 input seed points for the start and end position of the aorta. We validate our results against the ground truth manually extracted centerlines from para-sagittal PC images and anatomical MR images. The resulting measurement values of both centerline length and PWV show high accuracy and low variability, which allows for use in clinical setting. The main advantage of our method is that it requires only velocity encoded PC image, while being able to process images encoded only in one direction.
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Acknowledgement
This work was supported by IWT Innovation Mandate spin-off project 130865: “WaVelocity: cardiovascular structure and flow analysis software” and by Croatian Science Foundation under the project UIP-2017-05-4968.
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Babin, D. et al. (2020). Segmentation of Phase-Contrast MR Images for Aortic Pulse Wave Velocity Measurements. In: Blanc-Talon, J., Delmas, P., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2020. Lecture Notes in Computer Science(), vol 12002. Springer, Cham. https://doi.org/10.1007/978-3-030-40605-9_7
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DOI: https://doi.org/10.1007/978-3-030-40605-9_7
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