WP2 Cardio-thoracic imaging
Cardio-thoracic imaging has shown tremendous progress over the last decade. Rapid (highly subsampled) acquisition techniques and optimized reconstruction algorithms addressed cardiac contraction and respiratory motion issues. Thus, high-resolution 3D cardiac and lung MRI, in complement to CT imaging, has opened up new possibilities for better description of tissue alteration and better therapeutic follow-up.
Crédits photo - Graduate Program Cardiac EP
In this perspective, the WP2 teams aim to develop a new contrast at an early step (WP2-1) while stimulating AI-based image processing to help the methods already available (WP2-2).
WP2-1: Developing manganese-enhanced imaging for heart and lung imaging
- General objectives – to develop manganese-based MRI for both pulmonary and cardiac imaging and evaluate them in animal models.
- WP leaders – Yannick Cremillieux (ISM) ; Aurélien Trotier, Julie Magat (CRMSB/IHU liryc)
- PhD candidate – Alexis Rotondi (supervisors : Bruno Quesson, Dounia El Hamrani)
- Engineer – Georgina Jesuthasan (supervisor : Yannick Crémillieux)
WP2-2: Deep learning to improve MR lung imaging
- General objectives:
- to develop an AI algorithm to enable CT-like imaging quality from lung MRI with ultrashort echo times and to generalize the developed algorithm to images from the main MR manufacturers
- to set AI-based quantifications in such synthetic lung MRI images
- to assess the clinical validity of the developed methods in a cohort of patients with chronic airway disease, both cross-sectionally and longitudinally.
- WP leaders – Gaël Dournes, François Laurent, Patrick Berger, Llyes Benlala (CRCTB) ; Fabien Baldacci (LaBRI) ; Baudoin Denis de Senneville (IMB)
- PhD candidate – Amèle Imène Hadj Bouzid (surpervisor : Gaël Dournes)
Research staff
- ">