Meeting Banner
Abstract #5238

Deep learning based segmentation of cardiomyocytes to aid numerical simulations of diffusion cardiovascular magnetic resonance

Jan N Rose1, Wee Zhao Chua Khoo1, Sonia Nielles-Vallespin2,3, Pedro F Ferreira3, David N Firmin3, Andrew D Scott3, and Denis J Doorly1

1Aeronautics, Imperial College London, London, United Kingdom, 2National Institute of Health, Bethesda, MD, United States, 3CMR Unit, Royal Brompton Hospital, London, United Kingdom

To better understand how the underlying microstructure and pathology affect the DT-CMR signal in vivo, more realistic numerical models that account for irregular myocyte configurations such as sheetlets are necessary. We manually segmented cardiomyocytes from pig histology and confirmed that the resulting substrate is representative of the local microstructure through automatic segmentation of the surrounding tissue with a convolutional neural network. Monte Carlo random walk simulations, covering short and long mixing times and varying compartment diffusivities, show a mismatch between the results for the histology-based substrate and a simple cuboid model with comparable ECV and mean cell size.

This abstract and the presentation materials are available to members only; a login is required.

Join Here