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  • Gallery of Fluid Motion
  • Open Access
  • Access by Xinjiang University

Spectral landscapes of flow instabilities in brain aneurysms

Thangam Natarajan1, Daniel E. MacDonald1, Lucas Temor1, Peter W. Coppin2, and David A. Steinman1,*

  • 1Department of Mechanical and Industrial Engineering, Biomedical Simulation Laboratory, University of Toronto, Toronto, Ontario, Canada
  • 2Perceptual Artifacts Laboratory, OCAD University, Toronto, Ontario, Canada

  • *Corresponding author: steinman@mie.utoronto.ca
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Phys. Rev. Fluids 6, 110505 – Published 15 November, 2021

DOI: https://doi.org/10.1103/PhysRevFluids.6.110505

Abstract

This paper is associated with a poster winner of a 2020 American Physical Society's Division of Fluid Dynamics (DFD) Milton van Dyke Award for work presented at the DFD Gallery of Fluid Motion. The original poster is available online at the Gallery of Fluid Motion, https://doi.org/10.1103/APS.DFD.2020.GFM.P0004.

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2020 Gallery of Fluid Motion

Collection of papers associated with the 2020 Gallery of Fluid Motion. These award winning works were presented at the annual meeting of the APS Division of Fluid Dynamics.

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References (11)

  1. K. Valen-Sendstad and D. A. Steinman, Mind the gap: impact of computational fluid dynamics solution strategy on prediction of intracranial aneurysm hemodynamics and rupture status indicators, Am. J. Neuroradiology 35, 536 (2014).
  2. Aneuriskweb, the aneurisk dataset repository, http://ecm2.mathcs.emory.edu/aneuriskweb/index. Accessed: 2021-08-03.
  3. M. O. Khan, V. T. Arana, M. Najafi, D. E. MacDonald, T. Natarajan, K. Valen-Sendstad, and D. A. Steinman, On the prevalence of flow instabilities from high-fidelity computational fluid dynamics of intracranial bifurcation aneurysms, J. Biomech. 127, 110683 (2021).
  4. D. A. Steinman and V. M. Pereira, How patient specific are patient-specific computational models of cerebral aneurysms? An overview of sources of error and variability, Neurosurgical Focus 47, E14 (2019).
  5. T. Natarajan, D. E. MacDonald, M. Najafi, P. W. Coppin, and D. A. Steinman, Spectral decomposition and illustration-inspired visualisation of highly disturbed cerebrovascular blood flow dynamics, Comput. Methods Biomech. Biomed. Eng.: Imaging Vis. 8, 182 (2020).
  6. U. Ayachit, The ParaView Guide: A Parallel Visualization Application (Kitware, Inc., New York, 2015).
  7. Blender Online Community, Blender-A 3D Modelling and Rendering Package (Blender Foundation, Blender Institute, Amsterdam, 2017).
  8. T. Natarajan, D. E. MacDonald, M. Najafi, M. O. Khan, and D. A. Steinman, On the spectrographic representation of cardiovascular flow instabilities, J. Biomech. 110, 109977 (2020).
  9. t-SNE visualization of CNN codes, https://cs.stanford.edu/people/karpathy/cnnembed/. Accessed: 2021-08-03.
  10. PyTorch VGG-NETS, https://pytorch.org/hub/pytorch_vision_vgg/. Accessed: 2021-08-03.
  11. D. A. Steinman, P. W. Coppin, and D. A. Steinman, Narcissus and echo: Reflections on an art-science collaboration, Leonardo 54, 552 (2021).

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Phys. Rev. Fluids 6, 110505– Published 15 November, 2021
  • Received 6 August 2021
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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