363-06-005 ISMRM Abstract

Image2Flow Transient: Fast Estimation of Transient Pulmonary Artery Flow Fields from 3D Cardiac MRI

Primary: Analysis Methods - Segmentation and Detection

Secondary: Cardiovascular - Flow

363-06-005 · Hemodynamics and Flow · Monday, 11 May, 5:05 PM–6:00 PM · Digital Posters Row D

Keywords: Flow Deep Learning Segmentation CONVOLUTIONAL NEURAL NETWORK Computational Fluid Dynamics Graph Neural Networks

Accepted

Anirudh Raman ¹, Tina Yao¹, Jennifer Steeden^1,2, Vivek Muthurangu¹

¹University College London, London, United Kingdom

²Center for Cardiovascular Imaging, United Kingdom

Presenting Author: Anirudh Raman

Synopsis

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References

1. T. Yao, E. Pajaziti, M. Quail, S. Schievano, J. Steeden, and V. Muthurangu, “Image2Flow: A proof-of-concept hybrid image and graph convolutional neural network for rapid patient-specific pulmonary artery segmentation and CFD flow field calculation from 3D cardiac MRI data,” PLoS Comput Biol, vol. 20, no. 6 June, Jun. 2024, doi: 10.1371/journal.pcbi.1012231. [doi]

2. X. Zhuang et al., “Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge,” Med Image Anal, vol. 58, Dec. 2019, doi: 10.1016/j.media.2019.101537. [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/363-06-005