Postdoctoral Opportunity: Multimodal MRI registration and analysis
Context and methodology
This postdoctoral position will focus on the registration of ex-vivo onto
in-vivo MR data. Based on some recent advances extending the combined volume
and surface registration, efficient approaches can be provided for dealing with
this issue. However, these methods need to be validated and several open
theoretical questions are related to this problem and will be investigated
during this postdoctoral work. The theoretical results obtained will be tested
and used on real human data in a larger framework aiming at tractography
validation (French National Research Agency Grant ANR 2014, collaborative study
Inserm U930, Université de Tours, Neurospin and Martinos Center).
Applicant profile
Candidates should have a strong background in image registration and MR
imaging, a good publication record, and strong experience in c++ and matlab
coding. Proficiency in English is required, as well as scientific writing
skills.
Applicants should send a CV, including list of publications and a description
of previous research experience, as well as the names and emails of two
academic referees to: Clovis Tauber (clovis.tau...@univ-tours.fr
<mailto:clovis.tau...@univ-tours.fr>) and Christophe Destrieux
(christophe.destri...@univtours.fr <mailto:christophe.destri...@univtours.fr> )
Conditions
Starting date: January 2016 (adjustable)
Contract: 2 years
Location: Imaging and Brain unit, INSERM U930, Tours.
Salary: related to experience
References
G.M. Postelnicu, L. Zöllei, B. Fischl: Combined Volumetric and Surface
Registration, IEEE Transactions on Medical Imaging 28 (4), April 2009, p.
508--522
Zemmoura I, Serres B, Andersson F, Barrantin L, Tauber C, Filipiak I, Cottier
JP, Venturini G and Destrieux C 2014 FIBRASCAN: a novel method for 3D white
matter tract reconstruction in MR space from cadaveric dissection Neuroimage
103 106—118
Serres B, Zemmoura I, Andersson F, Tauber C, Destrieux C and Venturini G 2013
Brain Virtual Dissection and White Matter 3D Visualization Stud. Health
Technol. Inform. 184 392--396
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