The Biovision Lab aims at developing fundamental research as well as technological developments along two axes.

Axis 1: High tech systems for low-vision patients

In 2015, 405 million people were visually impaired around the globe, against ‘only‘ 285 million in 2010. Almost half of it could have been prevented by earlier interventions in the form of treatment or rehabilitation. Because of aging, and its strong correlation with eye disease prevalence, this number is only expected to grow. To address this global health problem, actions must be taken to design effective solutions for earlier and more decisive detection of visual pathologies. There is a strong need to conceive new aid-systems to help these people in their daily living activities.

In Biovision we investigate new solutions for the visually impaired with three main goals:

  1. Designing solutions for earlier and more decisive detection of visual pathologies,
  2. Developing efficient rehabilitation protocols and
  3. Designing innovative vision-aid systems to empower patients with improved perceptual capacities.

To do this, we need to work in synergy with patients to assess their needs, understand their pathologies at a perceptual level and design personalized solutions to create change and adoption. This will require developing state-of-the-art methods in computer science, necessitating skills from many areas such as artificial intelligence, virtual and augmented reality, human-machine interface, multimedia systems, etc. By doing so, we will leverage new technologies to offer life-changing solutions for people with visual impairment.

Axis 2: Human vision understanding through joint experimental and modeling studies, for normal and dystrophic retinas

A holistic point of view is emerging in neuroscience where one can observe simultaneously how vision works at different levels of the hierarchy in the visual system. Multiple scales functional analysis and connectomics are also exploding in brain science, and studies of visual systems are upfront on this fast move. These integrated studies call for new classes of theoretical and integrated models where the goal is the modeling of visual functions such as motion integration.

In Biovision we contribute to a better understanding of the visual system with four main goals:

  1.  Proposing simplified mathematical models characterizing how the retina converts a visual scene into spike population coding, in normal and under specific pathological conditions.

  2.  Designing biophysical models allowing to better understand the multiscale dynamics of the retina, from dynamics of individual cells to their collective activity, and how changes in biophysical parameters (development, pharmacology, pathology) impacts this dynamics.

  3.  Designing an integrated numerical model of the visual stream, with a focus on motion integration, from the retina to early visual cortex (V1).

  4.  Developing a simulation platform emulating the retinal spike-response to visual and prosthetic simulations, in normal and pathological conditions.

Finally, although this is not the main goal of our team, another natural avenue of our research will be to develop novel synergistic solutions to solve computer vision tasks based on bio-inspired mechanisms.

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