Biovision team
2
Retina Visual cortex 3
Retina Visual cortex 3
Retina Visual cortex 3
Retina Visual cortex 3
285 millions visually impaired people Retina Visual cortex 3
285 millions visually impaired people Retina Visual cortex New technics are emerging to help people use their remaining vision, slow down or even reverse vision loss New scientific and technological challenges New paradigms to understand vision New technological breakthroughs 3
Visual impairment examples From low vision to blindness 4
Visual impairment examples From low vision to blindness Retinitis Pigmentosa (rods photoreceptors degenerate) Age Related Macular Degeneration (macula cones degenerate) Glaucoma (ganglion cells and the optic nerve degenerate) Degenerative myopia (major alteration of the shape or globe of the eye) 4
Visual impairment examples From low vision to blindness Retinitis Pigmentosa (rods photoreceptors degenerate) Age Related Macular Degeneration (macula cones degenerate) Glaucoma (ganglion cells and the optic nerve degenerate) Degenerative myopia (major alteration of the shape or globe of the eye) 4
Low vision Main existing tools for accessibility: Magnifiers Optical devices Electronic magnifiers Immersive systems 5
Blindness Existing emerging therapeutic methods 6
Blindness Existing emerging therapeutic methods Gene therapy Stem cells Cell transplantation Retinal prostheses (electric, optoelectronic, optogenetic) 6
Blindness Existing emerging therapeutic methods Gene therapy Stem cells Cell transplantation Retinal prostheses (electric, optoelectronic, optogenetic) Camera Receiver Processor 6
Blindness Existing emerging therapeutic methods Gene therapy Stem cells Cell transplantation Retinal prostheses (electric, optoelectronic, optogenetic) Camera Receiver Processor 6
Blindness Existing emerging therapeutic methods Gene therapy Stem cells Cell transplantation Retinal prostheses (electric, optoelectronic, optogenetic) Photoreceptors Camera Receiver Processor 6
Blindness Existing emerging therapeutic methods Gene therapy Stem cells Cell transplantation Retinal prostheses (electric, optoelectronic, optogenetic) Photoreceptors Camera Receiver Processor Ganglion cells 6
Biovision team Helping visually impaired people High scientific, technologic, societal, economic impact New institutes, start-ups, companies However, fundamental issues remain unresolved 7
Biovision team Helping visually impaired people High scientific, technologic, societal, economic impact New institutes, start-ups, companies However, fundamental issues remain unresolved 7
Biovision team Helping visually impaired people High scientific, technologic, societal, economic impact New institutes, start-ups, companies However, fundamental issues remain unresolved Computational neuroscience Mathematical Biophysical analysis modelling Computer vision Neuroscientists and physicians 7
Fundamental research 8
Fundamental research Scene analysis Scene enhancement (dependent on pathology) 8
Fundamental research Methods from computer Scene analysis vision and graphics Scene enhancement (dependent on pathology) 8
Fundamental research Methods from computer Scene analysis vision and graphics Scene enhancement (dependent on pathology) Retina processing Encoding Stimulation 8
Fundamental research Methods from computer Scene analysis vision and graphics Scene enhancement (dependent on pathology) Biophysical modeling Information compression Retina emulation Retina processing Encoding Stimulation 8
Fundamental research Methods from computer Scene analysis vision and graphics Feedback Scene enhancement Perception (dependent on pathology) Biophysical modeling Information compression Retina emulation Retina processing Encoding Stimulation 8
Software development 9
Software development Producing software for biologists and physicians 9
Software development Producing software for biologists and physicians ENAS : A software for analysing spike trains at single cell and population levels Cessac et al. (in preparation) ADT, ANR KEOPS, FP7 Renvision https://enas.inria.fr Virtual Retina : A large scale simulator of biological retina Wohrer, Kornprobst (2007) http://www-sop.inria.fr/neuromathcomp/public/software/virtualretina/ 9
Software development Producing software for biologists and physicians ENAS : A software for analysing spike trains at single cell and population levels Cessac et al. (in preparation) ADT, ANR KEOPS, FP7 Renvision https://enas.inria.fr Virtual Retina : A large scale simulator of biological retina Wohrer, Kornprobst (2007) http://www-sop.inria.fr/neuromathcomp/public/software/virtualretina/ 9
Software development Producing software for biologists and physicians ENAS : A software for analysing spike trains at single cell and population levels Cessac et al. (in preparation) ADT, ANR KEOPS, FP7 Renvision https://enas.inria.fr Virtual Retina : A large scale simulator of biological retina Wohrer, Kornprobst (2007) http://www-sop.inria.fr/neuromathcomp/public/software/virtualretina/ New vision-aid systems for patients with impaired vision 9
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Receptive fields estimation University of Newcastle RENVISION EU project (ends 2016) University of Edinburgh 10
Receptive fields estimation University of Newcastle RENVISION EU project (ends 2016) University of Edinburgh Anything moving? Local edge? 10
Receptive fields estimation New variational approaches for receptive estimation (ongoing) A. Drogoul New method for stimuli design (started) Enas implementation 11
Spike coding ADT (2012-2014) University of Valparaiso ANR KEOPS (2011-2015) Institut de la vision RENVISION project (ends 2016) 12
Spike coding ADT (2012-2014) University of Valparaiso ANR KEOPS (2011-2015) Institut de la vision RENVISION project (ends 2016) Neurons Time (ms) 12
Spike coding 13
Spike coding How do stimuli and connectivity shape the collective retina response? 13
Spike coding How do stimuli and connectivity shape the collective retina response? Handling spatio-temporal correlations and non-stationary response to stimuli 13
Spike coding How do stimuli and connectivity shape the collective retina response? Handling spatio-temporal correlations and non-stationary response to stimuli Experimental studies and analysis 13
Spike coding How do stimuli and connectivity shape the collective retina response? Handling spatio-temporal correlations and non-stationary response to stimuli Experimental studies and analysis Enas implementation 13
Application to retina prosthesis? 14
Application to retina prosthesis? 14
Application to retina prosthesis? 64 pixels - Argus II Adapted from Institut de la Vision 14
Application to retina prosthesis? 256 pixels 64 pixels - Argus II Adapted from Institut de la Vision 14
Application to retina prosthesis? 1024 pixels 256 pixels 64 pixels - Argus II Adapted from Institut de la Vision 14
Application to retina prosthesis? 15
Application to retina prosthesis? 15
Scene transforms in computer vision and graphics Designed for artistic purposes 16
Scene transforms in computer vision and graphics Designed for artistic purposes Example: Image and video quality improvements: Equalisation, gamma correction, tone mapping, edge enhancement, image decomposition, cartoonization Source XDoG XDoG Thresh. Winnemoller et al. (2012) 16
Scene transforms in computer vision and graphics For retina prosthesis and low vision Designed for artistic purposes Example: Image and video quality improvements: Equalisation, gamma correction, tone mapping, edge enhancement, image decomposition, cartoonization Source XDoG XDoG Thresh. Winnemoller et al. (2012) 16
Scene transforms in computer vision and graphics For retina prosthesis and low vision Example of problem Disambiguate what comes from structure and what comes from illumination 17
Scene transforms in computer vision and graphics For retina prosthesis and low vision Example of problem Disambiguate what comes from structure and what comes from illumination 17
Methods from computer Scene analysis vision and graphics Scene enhancement (dependent on pathology) Biophysical modeling Information compression Retina emulation Retina processing Encoding Stimulation 18
Methods from computer Scene analysis vision and graphics Scene enhancement (dependent on pathology) Biophysical modeling Information compression Retina emulation Retina processing Encoding Stimulation 19
Methods from computer Scene analysis vision and graphics Feedback Scene enhancement Perception (dependent on pathology) Biophysical modeling Information compression Retina emulation Retina processing Encoding Stimulation 19
Synergistic model of motion processing INT Institut de la Vision ANR Trajectory (M2+PhD, 2015-2018) University of Valparaiso K. Medathati PhD (2013-2016) ULM University 20
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