> 10. Machine Learning, Bioinformatics, Image and signal Processing

Chairs:Christian Daul, University of Lorraine, France (coordinator)

Yuri Kistenev, Tomsk University, Russia, July Galeano, Instituto Tecnológico Metropolitano. Medellín, Colombia, Franck Marzani, Université de Bourgogne, France, Walter Blondel, University of Lorraine, France

This session deals with all simulation and modelling, machine learning and deep-learning techniques relating to the processing, analysis, understanding and interpretation of signals and images acquired with spectroscopic, imaging, laser based or biophotonic sensing devices. A particular focus is done on monomodal, multimodal and nonconventional systems such as multispectral, supplemented by data segmentation, fusion, analysis and classicication of signals for lesion diagnosis or treatment of all types of human tissues.

Aydogan Ozcan, University of California, Los Angeles, USA

Deep learning-enabled computational microscopy and sensing


Yury Kistenev, Tomsk University, Russia

Molecular imaging and machine learning


Yannick Benezeth, Université de Bourgogne, France

Automated detection of stomach lesions by endoscopic imaging: comparison of NBI and multispectral images


Alexander Kel, geneXplain GmbH, Germany

Application of machine learning in Bioinformatics towards drug target discovery


Thomas Mangeat, CNRS - CBI (Center for Integrative Biology) - Paul Sabatier University - Toulouse III, France

Super-resolved live imaging for a wide range of biological applications using Random Illumination Microscopy (RIM)



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