[visionlist] Master 2 internship position: medical imaging/machine learning at university of Poitiers, France

[Olfa Ben Ahmed]

The university of Poitiers and the XLIM institute are offering an 
internship position of 6 months in medical imaging and machine learning 
for Alzheimer's disease diagnosis.

*Title :* Classification of Alzheimer’s disease subjects using 
Spectroscopy data

*Scientific context:*
Alzheimer’s disease (AD) is the most comment form of dementia. 
Neuroimaging data is an integral part of the clinical assessment 
providing a way for clinicians to detect brain abnormalities for AD 
diagnosis.  Structural MRI with machine learning techniques has been 
widely studied to assess brain atrophy for AD detection and prediction 
[1][2].   In addition to structural changes, metabolic changes in some 
brain regions could be a good biomarker for an early AD [3].  Recently, 
Magnetic Resonance Spectroscopy (MRS) have been proved to be effective 
to quantify certain brain metabolites in vivo [4]. The proposed 
internship aims in testing and evaluating the effectiveness of machine 
learning techniques for single subject level classification of 
individuals affected by different stages of AD (healthy elderly 
subjects, Mild Cognitive Impairment (MCI) and AD subjects) based on 1H 
MRS data.  Data used in this internship are provided by CHU of Poitiers.

*Objectives:*
-Evaluate and compare several machine learning algorithms for AD 
spectroscopy data classification
-Propose solution for learning from few data of spectroscopy data for AD 
subject’s classification.
-Jointly Investigate the structural and metabolic changes associated 
with incipient AD pathology to improve MCI subject’s detection.

*References:*
[1] Olfa Ben Ahmed et al "Recognition of Alzheimer's Disease and Mild 
Cognitive Impairment with multimodal image-derived biomarkers and 
Multiple Kernel Learning", International Journal Neurocomputing, vol. 
220, p. 98-110, Elsevier 2017
[2] Sarraf, S., Tofighi, G.,. DeepAD: Alzheimer′s Disease Classification 
via Deep Convolutional Neural Networks using MRI and fMRI. bioRxiv  2016
[3] Wang Z, Zhao C, Yu L, et al Regional metabolic changes in the 
hippocampus and posterior cingulated area detected with 3-Tesla magnetic 
resonance spectroscopy in patients with mild cognitive impairment and 
Alzheimer's disease. Acta Radiol 2009;50:312–19
[4] Pedro J Modrego et al. Magnetic resonance spectroscopy in the 
prediction of early conversion from amnestic mild cognitive impairment 
to dementia: a prospective cohort study. BMJ Open 1, e000007.

*Key Words*: Alzheimer, MRI, spectroscopy, Artificial Intelligence, 
Machine learning, information fusion, classification

*Skills:*
MS student in Computer Science,  Image and signal processing, machine 
learning or related streams.
Strong knowledge in at least one of the following fields is required:

         • good image processing and machine learning knowledge
         • mathematical understanding of the formal background
         • excellent programming skills (Python, C++, MATLAB)
         • biomedical applications would be appreciated

*Salary*: 560€/ Month

*Application: *interested candidates should send their CV and a cover 
letter to olfa.ben.ahmed at univ-poitiers.fr 
<mailto:olfa.ben.ahmed at univ-poitiers.fr>

-- 

Dr. Olfa BEN AHMED
Associate professor
XLIM - University of Poitiers

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