ADVANCES : Automatic detection of viable myocardiac segments considering deep networks
Porteurs d’ImViA : Alain LALANDE Site web : https://anr.fr/Projet-ANR-18-CE33-0004 Partenaires : I3S-INRIA/LITIS Début du projet : 2018 Fin du projet : 2022
Myocardial infarction (MI) is an important cause of death worldwide. ADVANCES
Résumé :
One crucial parameter to evaluate the state of the heart after MI is the
viability of the myocardial segment, i.e. if the segment can recover
functionally upon revascularization. MRI acquired several minutes after
injection of a contrast agent
(DE-MRI) is a method of choice to evaluate the extent of MI, and by extension, to assess viable tissues after injury.
aims at automatically detecting the different relevant areas using deep
learning approaches from a series of short-axis DE-MRI covering the
left ventricle and then to make a quantification of the MI. The
developped tool will be included in a dedicated and certified software
available for the medical community.
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- COMUE
- nom_du_projet:
- Automatic detection of viable myocardiac segments considering deep networks
- porteur:
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