News - Thesis announce

Date : Feb. 21, 2019, 2 p.m. - ANGELETTI Mélodie - Amphi Garcia

Processing of multi-spectral data by high performance computing and its applications on human MRI

As a non-invasive technology for studying brain imaging, functional magnetic resonance imaging (fMRI) has been employed to understand the brain underlying mechanisms of food intake. Using liquid stimuli to fake food intake adds difficulties which are not present in fMRI studies with visual stimuli. This PhD thesis aims to propose a robust method to analyse food stimulated fMRI data. To correct the data from swallowing movements, we have proposed to censure the data uniquely from the measured signal. We have also improved the normalization step of data between subjects to reduce signal loss.

The main contribution of this thesis is the implementation of Ward's algorithm without data reduction. Thus, clustering the whole brain in several hours is now feasible. Because Euclidean distance computation is the main part of Ward algorithm, we have developed a cache-aware algorithm to compute the distance between each pair of voxels. Then, we have parallelized this algorithm for three architectures: shared-memory architecture, distributed memory architecture and NVIDIA GPGPU.

Once Ward's algorithm has been applied, it is possible to explore multi-scale clustering of data. Several criteria are considered in order to evaluate the quality of clusters. For a given number of clusters, we have proposed to compute functional connectivity maps between clusters or to compute Pearson correlation coefficient to identify brain regions activated by the stimulation.

Keywords: food fMRI, multi-scale clustering, Ward's algorithm, Euclidean distance, Parallelization, OpenMP, MPI, CUDA.

 

Jury:

M. Jean-Marie BONNY, Research Director, INRA de Théix, Thesis director,
Mme Camille COTI, Associate Professor, Laboratoire d'Informatique de Paris Nord, Université Paris XIII, Assessor;
M. Raphaël COUTURIER, Professor, IUT de Belfort-Montbéliard , Université de Franche-Comté, Reviewer;
M. Franck DURIF, Professor, Service de Neuroscience CHU Gabriel-Montpied, Université Clermont Auvergne, Assessor;
M. Jonas KOKO, Associate Professor, LIMOS, Université Clermont Auvergne, Thesis director
Mme Évelyne LUTTON, Research director, INRA- Agro-Paris Tech, Reviewer,
Mme Hélène TOUSSAINT, Research engineer LIMOS, Université Clermont-Auvergne, Assessor;
Mme Charlotte SINDING, Researcher, INRA Dijon, Assessor.