ArticleJournal of vision2022
End-to-end optimization of prosthetic vision.
Article in Journal of vision, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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Who cites it
22 citing papers in PubMed, 50 citations in OpenAlex.
- Evaluating the Efficacy of Smart Saliency Detection System for Visual Prosthesis Users: An Experimental Comparison Across Various Visual Prosthesis Implants.Artificial organs · 2026Article
- Article
- Fuzzing the brain: automated stress testing for the safety of ML-driven neurostimulation.Journal of neural engineering · 2026Article
- Deep Learning-Based Control of Electrically Evoked Activity in Human Visual Cortex.bioRxiv : the preprint server for biology · 2025Article
- Evaluating Deep Human-in-the-Loop Optimization for Retinal Implants Using Sighted Participants.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2025Article
- Visual Prostheses in the Era of Artificial Intelligence Technology.Eye and brain · 2025Review
- Point-SPV: end-to-end enhancement of object recognition in simulated prosthetic vision using synthetic viewing points.Frontiers in human neuroscience · 2025Article
- Article
- Aligning Visual Prosthetic Development With Implantee Needs.Translational vision science & technology · 2024Article
- Aligning visual prosthetic development with implantee needs.medRxiv : the preprint server for health sciences · 2024Article
- Predicting the Temporal Dynamics of Prosthetic Vision.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2024Article
- Axonal stimulation affects the linear summation of single-point perception in three Argus II users.Journal of neural engineering · 2024Article
- Article
- An actor-model framework for visual sensory encoding.Nature communications · 2024Article
- Neuromorphic hardware for somatosensory neuroprostheses.Nature communications · 2024Review
- Axonal stimulation affects the linear summation of single-point perception in three Argus II users.medRxiv : the preprint server for health sciences · 2023Article
- Human-in-the-Loop Optimization for Deep Stimulus Encoding in Visual Prostheses.Advances in neural information processing systems · 2023Article
- A novel simulation paradigm utilising MRI-derived phosphene maps for cortical prosthetic vision.Journal of neural engineering · 2023Article
- Towards aJournal of neural engineering · 2022Article
- Hybrid Neural Autoencoders for Stimulus Encoding in Visual and Other Sensory Neuroprostheses.Advances in neural information processing systems · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neural prosthetics may provide a promising solution to restore visual perception in some forms of blindness. The restored prosthetic percept is rudimentary compared to normal vision and can be optimized with a variety of image preprocessing techniques to maximize relevant information transfer. Extracting the most useful features from a visual scene is a nontrivial task and optimal preprocessing choices strongly depend on the context. Despite rapid advancements in deep learning, research currently faces a difficult challenge in finding a general and automated preprocessing strategy that can be tailored to specific tasks or user requirements. In this paper, we present a novel deep learning approach that explicitly addresses this issue by optimizing the entire process of phosphene generation in an end-to-end fashion. The proposed model is based on a deep auto-encoder architecture and includes a highly adjustable simulation module of prosthetic vision. In computational validation experiments, we show that such an approach is able to automatically find a task-specific stimulation protocol. The results of these proof-of-principle experiments illustrate the potential of end-to-end optimization for prosthetic vision. The presented approach is highly modular and our approach could be extended to automated dynamic optimization of prosthetic vision for everyday tasks, given any specific constraints, accommodating individual requirements of the end-user.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.