Team IMAGeS - IMages, leArning, Geometry and Statistics

Biomedical image processing

From Team IMAGeS - IMages, leArning, Geometry and Statistics
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Head Vincent Noblet
Co-head Denis Fortun
Investigators: Etienne Baudrier, Christophe Collet, Caroline Essert, Sylvain Faisan, Christian Heinrich, Fabrice Heitz, Ernest Hirsch, Adrien Krähenbühl, Alex Lallement, Aurélie Leborgne, Céline Meillier, Nicolas Meyer, Philippe Meyer, Benoit Naegel, Mickael Ohana, Erik-André Sauleau, Mohamed Tajine, Laurent Thoraval, Jimmy Voirin
Ph. D. students: Arnaud Abreu, Pietro Addeo, Romel Bhattacharjee, Argheesh Bhanot, Anastasiia Bozhok, Elena Chabran, Iris Daurensan, Eléonore Dufresne, Hugo Gangloff, Cyril Meyer, Farid Oumich, Florian Tilquin
Post doc:


Objectives

This theme aims at developing models, methods and algorithms for processing data from various medical and biological imaging systems:

  • Magnetic resonance imaging (structural, diffusion, angiography, functional ...)
  • Nuclear Medicine Imaging
  • CT scan
  • Electron microscopy
  • histology
  • polarimetric imaging
  • Etc.
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The goal is to develop image processing methods for the study of living at different scales in the case of pre-clinical (small animal imaging) and clinical (human imaging) data:

  • microscopic scale: macromolecules reconstruction from electron microscopy, cellular image analysis with the FIB / SEM technology, ...
  • mesoscopic scale: Histopathological data analysis, study of biological tissues using polarimetric imaging, ...
  • macroscopic scale: study of brain connectivity, ...

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Context and application areas

All these works are carried out in close collaboration with biologists, doctors and researchers in neuroscience, with strong interactions with the team IMIS. These activities are part of the transverse axis Imaging and Medical and Surgical Robotics (IRMC), and integrate partly into the Federation of Translational Medicine of Strasbourg (FMTS) and the IHU of Strasbourg. A close link also exists with the acquisition of images, in particular thanks to the privileged access to the laboratory platform Imagines.

The main challenges related to the developed tools are both to improve the patient care (personalized medicine), whether for the diagnosis, prognosis or evaluation of a therapeutic response, and to develop new knowledge, especially in Neurosciences. The main areas of application are:

  • The study of maturation and cerebral aging
  • Neurodegenerative pathologies (Alzheimer's disease, Lewy body dementia)
  • Inflammatory diseases of the central nervous system (multiple sclerosis, neuromyelitis optica)
  • Cancers (glioblastomas, hepatocarcinomas)

Research topics

The research activities of the theme are structured around six topics:

Data reconstruction
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Segmentation
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Registration
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Change detection and prediction
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Group comparison
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Brain connectivity
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Publications