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Segmentation of phase-contrast MR images for aortic pulse wave velocity measurements

Danilo Babin (UGent) , Daniel Devos (UGent) , Ljiljana Platisa (UGent) , Ljubomir Jovanov (UGent) , Marija Habijan (UGent) , Hrvoje Leventić and Wilfried Philips (UGent)
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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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MLA
Babin, Danilo, et al. “Segmentation of Phase-Contrast MR Images for Aortic Pulse Wave Velocity Measurements.” Advanced Concepts for Intelligent Vision Systems - ACIVS 2020, edited by Jacques Blanc-Talon et al., vol. 12002, Springer, 2020, pp. 77–86, doi:10.1007/978-3-030-40605-9_7.
APA
Babin, D., Devos, D., Platisa, L., Jovanov, L., Habijan, M., Leventić, H., & Philips, W. (2020). Segmentation of phase-contrast MR images for aortic pulse wave velocity measurements. In J. Blanc-Talon, P. Delmas, W. Philips, D. Popescu, & P. Scheunders (Eds.), Advanced concepts for intelligent vision systems - ACIVS 2020 (Vol. 12002, pp. 77–86). https://doi.org/10.1007/978-3-030-40605-9_7
Chicago author-date
Babin, Danilo, Daniel Devos, Ljiljana Platisa, Ljubomir Jovanov, Marija Habijan, Hrvoje Leventić, and Wilfried Philips. 2020. “Segmentation of Phase-Contrast MR Images for Aortic Pulse Wave Velocity Measurements.” In Advanced Concepts for Intelligent Vision Systems - ACIVS 2020, edited by Jacques Blanc-Talon, Patrice Delmas, Wilfried Philips, Dan Popescu, and Paul Scheunders, 12002:77–86. Springer. https://doi.org/10.1007/978-3-030-40605-9_7.
Chicago author-date (all authors)
Babin, Danilo, Daniel Devos, Ljiljana Platisa, Ljubomir Jovanov, Marija Habijan, Hrvoje Leventić, and Wilfried Philips. 2020. “Segmentation of Phase-Contrast MR Images for Aortic Pulse Wave Velocity Measurements.” In Advanced Concepts for Intelligent Vision Systems - ACIVS 2020, ed by. Jacques Blanc-Talon, Patrice Delmas, Wilfried Philips, Dan Popescu, and Paul Scheunders, 12002:77–86. Springer. doi:10.1007/978-3-030-40605-9_7.
Vancouver
1.
Babin D, Devos D, Platisa L, Jovanov L, Habijan M, Leventić H, et al. Segmentation of phase-contrast MR images for aortic pulse wave velocity measurements. In: Blanc-Talon J, Delmas P, Philips W, Popescu D, Scheunders P, editors. Advanced concepts for intelligent vision systems - ACIVS 2020. Springer; 2020. p. 77–86.
IEEE
[1]
D. Babin et al., “Segmentation of phase-contrast MR images for aortic pulse wave velocity measurements,” in Advanced concepts for intelligent vision systems - ACIVS 2020, Auckland, New Zealand, 2020, vol. 12002, pp. 77–86.
@inproceedings{8691362,
  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.}},
  author       = {{Babin, Danilo and Devos, Daniel and Platisa, Ljiljana and Jovanov, Ljubomir and Habijan, Marija and Leventić, Hrvoje and Philips, Wilfried}},
  booktitle    = {{Advanced concepts for intelligent vision systems - ACIVS 2020}},
  editor       = {{Blanc-Talon, Jacques and Delmas, Patrice and Philips, Wilfried and Popescu, Dan and Scheunders, Paul}},
  isbn         = {{9783030406042}},
  issn         = {{0302-9743}},
  language     = {{eng}},
  location     = {{Auckland, New Zealand}},
  pages        = {{77--86}},
  publisher    = {{Springer}},
  title        = {{Segmentation of phase-contrast MR images for aortic pulse wave velocity measurements}},
  url          = {{http://doi.org/10.1007/978-3-030-40605-9_7}},
  volume       = {{12002}},
  year         = {{2020}},
}

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