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  2. Multi­‐parametric MRI data fusion for the characterization of myocardial infarcts

Multi­‐parametric MRI data fusion for the characterization of myocardial infarcts

Context: Cardiac imaging has a central role for myocardial infarct from diagnosis to patient management and follow-up after revascularization. Nonetheless, despite the abundance of available data, complex and essential information contained in the images are truncated or integrated in a subjective way. Within the MI-MIX project, we target the analysis of multi-parametric cardiac imaging data from magnetic resonance imaging (MRI) and the design of integrative tools to better understand the mechanisms of myocardial ischemia-reperfusion.

Figure: Overview of the integrative analysis targeted in the project.

Objectives: We plan to retrospectively explore large existing MRI studies that include multi-parametric imaging of myocardial damages and regular follow-up [BEL-16], with clinical researchers from CHU St Etienne, France. This includes developing and exploiting computational atlases tools to transport the multi-parametric data of each individual to a common reference, and statistical learning techniques to compare them within a population [DIF-19]. To better understand disease development and evolution with therapy and follow-up, we also plan to incorporate the temporality of acquisitions within the analysis, supported by the development of practical software tools to visualize and explore these data.

Profile: We look for a highly motivated post-doc candidate, with:

  •  Main background in machine learning with strong interests for medical imaging applications,
  •  or main background in medical imaging with solid engineering skills in image processing and analysis,
  •  Good programming skills (MATLAB, Python, or C/C++),
  • Fluent in English (reading, writing, speaking).

Practical information:

  • The postdoc is part of the MI-MIX project from the Fédération Française de Cardiologie (2020-2022, PI: N. Duchateau), which focuses on the analysis of myocardial infarcts from multi-parametric imaging data.
  •  It will take place at CREATIS Lyon, reference French lab in medical imaging, which consists of ~160 people grouped in 5 research teams. It will be supervised by N. Duchateau (Associate Professor) and P. Clarysse (Research Director), with strong interaction with clinical researchers from CHU St Etienne (P. Croisille - radiologist, and M. Viallon – medical physicist).
  • Duration: 18 months, possibility to start from spring 2020.

Contact: Send your CV, motivation letter, and references to: nicolas.duchateau@creatis.insa-lyon.fr

References:

[BEL-16] Belle L, Motreff P, Mangin L, et al. Comparison of Immediate With Delayed Stenting Using the Minimalist Immediate Mechanical Intervention Approach in Acute ST-Segment-Elevation Myocardial Infarction: The MIMI Study. Circ Cardiovasc Interv. 2016;9:e003388.

[DIF-19] Di Folco M, Duchateau N, Viallon M, et al. Caractérisation statistique de l’infarctus du myocarde pour la personnalisation de modèles géométriques de lésions. Congrès National d’Imagerie du Vivant, Paris, 2019.

 

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