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  2. ratiney
Hélène Ratiney

PhD, Directrice de Recherche CNRS/ Research Director at CNRS                                                                                                                    

Tel:+33 (0)4 72 43 89 51                                           

Email: helene.ratiney@creatis.insa-lyon.fr 
 


Hélène RATINEY, is a permanently employed scientist (CNRS Research Director). Her expertise is in signal processing dedicated to in vivo NMR spectroscopy (quantification methods, MRI/MRS - MRSI specific analysis, sampling strategies ).

Following an engineering degree in Electrical Engineering from ENSEEIHT, Toulouse, France, and a M.Sc. degree in Signal Processing from the National Polytechnic Institute of Toulouse (both obtained in 2001), Hélène Ratiney received the PhD degree in ‘signal and Image’ from the Lyon 1 University in October 2004. Her phD project was devoted to the development of quantification methods for 1D MRS short echo time in vivo spectroscopy (method QUEST).  During a post-doctoral position (2005-2007, PI Daniel Pelletier), she was involved in a longitudinal study (EPIC/GeneMSA) conducted at UCSF San Francisco, that has followed 500 people with multiple sclerosis each year since 2004 with the purpose of capturing changes and learning factors that control the evolution of the disease. Her main contribution consisted in developping quantification strategy for brain spectroscopic imaging data to reach tissue specific (white matter/ gray matter) biochemical information: metabolite T1, metabolite concentration. Since her return to France, she has been developing different projects in quantitative MRI / MRS with the common goal of using optimization methods to improve the acquisition and processing of MRI or MRS data, and to test them in preclinical or clinical studies. She passed her "HDR" (an accreditation to supervise students) in 2019.

She is currently working on 1) optimal control for in vivo MRI/MRS  2) MRI/MRS quantification including deep learning    3) X-nuclei spectroscopy and k-t space sampling

RESEARCH INTERESTS

parametric estimation, Cramér Rao Lower bounds, sparse data,  optimal control for MRI and in vivo MR spectroscopy , MR spectroscopic imaging , multi-dimensional spectroscopy , lipids, metabolites, in brain, liver, muscle

HAL - CV and Publications

ORCID: https://orcid.org/0000-0002-0662-2172

 

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