Meeting Banner
Abstract #5134

DeepCardioPlanner: Deep Learning-based tool for automatic CMR planning

Pedro Louro Costa Osório1, Markus Henningsson2,3,4, Alberto Gomez Herrero5,6, Rita G. Nunes1, and Teresa M. Correia6,7
1Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal, 2Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden, 3Centre for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden, 4MR Physics, Perspectum Ltd, Oxford, United Kingdom, 5Ultromics Ltd, Oxford, United Kingdom, 6School of Biomedical Engineering Imaging Sciences, King’s College London, London, United Kingdom, 7Centre for Marine Sciences - CCMAR, Faro, Portugal

Synopsis

Keywords: Heart, Machine Learning/Artificial Intelligence, View PlanningCardiac Magnetic Resonance (CMR) is a powerful technique which can be used to perform a comprehensive cardiac examination. However, its adoption is often limited to specialised centres, in part due to the need for highly trained operators to perform the complex procedures of determining the 4 standard cardiac planes: 2-, 3-, 4-chamber and short axis views. To automate view planning, a deep learning-based tool (DeepCardioPlanner) has been proposed to regress the view defining vectors from a rapidly acquired 3D image. It successfully takes advantage of multi-objective learning to allow accurate, fast and reproducible view prescriptions without any operator input.

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