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.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.

Keywords