Offre en lien avec l’Action/le Réseau : – — –/– — –
Laboratoire/Entreprise : LIFAT Tours France
Durée : 3 ans
Contact : jyramel@univ-tours.fr
Date limite de publication : 2022-07-15
Contexte :
PhD Title: Graph Neural Networks for morphofunctional analysis and comparison of brain structures
Supervisors
● Jean-Yves Ramel (PR HDR) – LIFAT Université de Tours
● Elodie Chaillou (CR HC HDR) – INRAE PRC
● En collaboration avec l’équipe iBrain, INSERM (C. Destrieux, F. Anderson)
Description
Nowadays, the development of brain imaging methods generates a considerable amount of morphological and
functional data. However, their exploration and comparison over time for an individual (development and aging),
between individuals (variability within the species), and even more so between different species have been done only
partially. We propose to model these data in the form of graphs, then to use recent approaches of artificial intelligence
to better analyze them.
This approach has already been initiated by a multidisciplinary consortium of researchers in neuroanatomy, biology
and computer science as well as neurosurgeons during the Regional projects NeuroGéo and Neuro2Co (LIFAT, INRAE,
INSERM). It led to the creation of SILA3D, a software platform (in free access) allowing the representation of anatomo-
functional data in the form of graphs thanks to an interactive semantic segmentation of images [1, 2].
Sujet :
In this context, the proposed thesis aims to create new algorithms for anatomical and functional analysis and
comparison of brain structures using recent deep neural networks techniques dedicated to graphs (GNN, geometric
deep learning …).
The general objectives of this thesis are:
– To specify different strategies for modeling the brain data as graphs. For this, morphological and functional data from
different imaging modalities, including structural MRI and tractography, will be combined using different approaches
to be defined. The PhD student will use two datasets already acquired: a) ex vivo high field MRI of the human brainstem
(iBrain and NeuroSpin) [5, 10]; b) in vivo MRI of growing lambs (PRC and PIXANIM) [8].
– To Investigate differences between individuals (human brainstem variability) and over time (monitoring lamb brain
development from birth to adulthood [7,8,9]). The PhD student will propose several graph comparison methods
exploiting recent advances in Deep Learning on Graphs (GNN) [3, 4, 11].
The scientific challenges associated with these objectives are (1) to develop new graph-based deep learning methods
for the detection and classification of particular substructures in an encephalon (semi-supervised classification of
nodes) [3, 11]; (2) to develop new graph-based deep learning methods for the comparison, discrimination, and
classification of encephalon (supervised or unsupervised classification of graphs) [4,11].
More information: https://lifat.univ-tours.fr/medias/fichier/offre-phd-gnnbrain2022_1648463721506-pdf
Profil du candidat :
Candidates must have an MSc or engineering degree in a field related to computer science or applied mathematics,
with strong programming skills (in particular with deep learning frameworks). Experience with medical image analysis
or brain analysis will be a plus. Candidates are expected to have abilities to write scientific reports and communicate
research results at conferences in English
Formation et compétences requises :
Applications should include the following documents in electronic format: i) A short motivation letter stating why you
are interested in this project, ii) A detailed CV describing your past education and research background related to the
position. iii) The transcripts for master degrees. iv) The contact information for references (do not include the
reference letters with your applications as we will only ask for the reference letters for short-listed candidates).
Please send your application package to jean-yves.ramel@univ-tours.fr and elodie.chaillou@inrae.fr
A first selection will occur and then interviews will be proposed between April and the end of May.
Adresse d’emploi :
The position will start in October 2022 with a salary of 1975 euros gross/month (legal amount for doctoral contracts
in France) and will be located in Tours, France (LIFAT Lab). Ideally located in the heart of France (Loire Valley), one hour from Paris
and 2.5 hours away from the Atlantic Ocean, Tours is a lively and dynamic city.