Rapprocher la recherche en intelligence artificielle de la routine clinique
Speaker : Sébastien Jodogne
September 20, 2021 - 1PM
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Accès et partages des ressources génétiques à l’heure de la digitalisation
Speaker : Sylvain Aubry et Christine Frison
June 28, 2021 - 1PM (English)
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April 2021 – Dounia Mulders
Dounia Mulders received the M.Sc. degree in Mathematical Engineering in 2016 and the Ph.D. degree in Engineering Science and Technology in 2020, both from UCLouvain. During her Ph.D., she worked on the design of experimental paradigms and signal filtering algorithms to probe thermal perception and associated brain responses in humans. She is now a Postdoctoral Research Fellow in the Fiete Lab at MIT, in the Department of Brain and Cognitive Sciences and the McGovern Institute. Her core research interests currently lie in exploring the computational principles governing sensory perception, using statistical models and artificial neural networks.
Computational methods for EEG recordings during periodic sensory stimulation
Understanding how the human brain processes sensory stimuli remains challenging. For this purpose, brain responses elicited by brief stimuli and recorded with scalp electroencephalography (EEG) have been widely considered. Besides, much less is known about the dynamics of EEG responses and subsequent...
March 2021 – Bernard Hanseeuw
Bernard Hanseeuw is a behavioral neurologist conducting research on
early Alzheimer’s disease with the aim of better caring for patients
with or at-risk for memory decline. He graduated with an MD (2007), PhD
(2012) from Université Catholique de Louvain. He then completed a
post-doctoral research fellowship in Reisa Sperling’s lab at Harvard
Medical School (Boston, USA) from 2014 to 2017. He is now Deputy Head of
the Memory Clinic at Saint-Luc University Hospital. He also holds the
positions of clinical Associate Professor at UCLouvain and Instructor in
Radiology at Harvard University. His research, supported by the
National Fund for Scientific Research (FNRS), the Queen Elizabeth
Medical Foundation (FMRE), the Belgian Foundation for Alzheimer’s
Research (SAO-FRA), the Fondation Saint-Luc and Fondation Louvain, was
awarded several prizes including: the ‘Horlait Dapsens’ and ‘Baron Simonart’ Foundations, ‘Prix d’excellence 2018 de la Société Française de Neurologie’ and the ‘Santkin Prize of the Belgian Royal Academy of Medicine’.
Dr. Hanseeuw directs the Louvain Aging Brain...
Artificial intelligence : perspectives in laboratory medicine
Speaker : Damien Gruson 1,2
1Department of Clinical Biochemistry,
Cliniques Universitaires St-Luc and Université Catholique de Louvain, Brussels,
Belgium.
2Pôle de recherche en Endocrinologie, Diabète
et Nutrition, Institut
de Recherche Expérimentale et Clinique, Cliniques Universitaires St-Luc and
Université Catholique de Louvain, Brussels, Belgium.
April 26, 2021 - 1PM (English)
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Feedback control and movement adaptation in (biological) neural networks
Speaker : Pr. Frédéric Crevecoeur
March 29, 2021 - 1PM (English)
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February 2021 – Jean Léger
Jean Léger received his Electrical Engineering Master’s degree from UCLouvain in 2016. He is currently F.R.S.-FNRS Research Fellow completing a PhD under the supervision of Prof. B. Macq and Prof. C. De Vleeschouwer. His research focuses on image segmentation with deep learning for biomedical applications. In such applications, datasets are often “imperfect” since annotations (and sometimes also data) required for supervised learning are hard to collect. Hence, the annotations are often scarce and/or noisy.
DEEP LEARNING-BASED SEGMENTATION OF MINERALIZED CARTILAGE AND BONE IN HIGH-RESOLUTION MICRO-CT IMAGES
One of Jean’s research projects aims at automatically segmenting mineralized cartilage from bone in micro-CT images (collaboration with Prof. G. Kerckhofs). Because of its function of mediating load between very dissimilar tissues, the bone-to-tendon interface is a common site of injury. However, in case of such injury, the natural tissue is not regenerated after healing. Instead, it is replaced with a so-called scar...
December 2020 – Eliott Brion
Eliott Brion has a master degree in Applied Mathematics jointly from UCLouvain and CentraleSupélec. He is currently pursuing the Ph.D. in Applied Science with UCLouvain, with a focus on deep learning for radiotherapy, supervised by Prof. B. Macq and Prof. J. Lee.
MEASURING ANATOMICAL VARIATIONS BETWEEN RADIOTHERAPY TREATMENT SESSIONS TO IMPROVE DOSE CONFORMITY
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Introducing TRusted AI Labs (TRAIL)
Speakers : Benoit Macq & Michel Verleysen.
November 28, 2020 - 1PM (French)
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Automated, fast and reliable analysis of pyrosequencing signals
Pyrosequencing is a DNA sequencing technology that has many applications including rapid genotyping of single nucleotide polymorphisms (SNP) and other sequence variations between different cells, individuals and species. Identifying the specific composition of microorganisms inside a microbial population may help choose the most specific treatment in case of infectious disease. Likewise, pyro-sequencing can also apply to the screening and identification of oncogenic mutations(s) in a heterogeneous sample containing tumour cells of interest in a background of wild type cells. Converting a pyrosequencing signal into a nucleotide sequence appears highly challenging when signal intensities are low (unitary peak heights <5) or when complex signals are produced by several target amplicons. In these cases, the pyrosequencing software fails to provide correct nucleotide sequences. At the CTMA (Center for Applied Molecular Technologies), researchers developed the AdvISER-PYRO, an algorithm based on a machine learning method (i.e., a sparse representation) to perform an automated, fast and reliable analysis of pyrosequencing signals which circumvents above...