Synthetic electroretinogram signal generation using a conditional generative adversarial network.
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| Title: | Synthetic electroretinogram signal generation using a conditional generative adversarial network. |
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| Authors: | Kulyabin M; Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany., Zhdanov A; VisioMed.AI, Moscow, Russia., Lee IO; Behavioural and Brain Sciences Unit, Population Policy and Practice Programme, UCL Great Ormond Street Institute of Child Health, University College London, London, UK., Skuse DH; Behavioural and Brain Sciences Unit, Population Policy and Practice Programme, UCL Great Ormond Street Institute of Child Health, University College London, London, UK., Thompson DA; The Tony Kriss Visual Electrophysiology Unit, Clinical and Academic, Department of Ophthalmology, Great Ormond Street Hospital for Children NHS Trust, London, UK.; UCL Great Ormond Street Institute of Child Health, University College London, London, UK., Maier A; Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany., Constable PA; College of Nursing and Health Sciences, Caring Futures Institute, Flinders University, Adelaide, 5000, Australia. paul.constable@flinders.edu.au. |
| Source: | Documenta ophthalmologica. Advances in ophthalmology [Doc Ophthalmol] 2025 Oct; Vol. 151 (2), pp. 161-177. Date of Electronic Publication: 2025 Apr 16. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Kluwer Country of Publication: Netherlands NLM ID: 0370667 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-2622 (Electronic) Linking ISSN: 00124486 NLM ISO Abbreviation: Doc Ophthalmol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1573-2622 |
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| DOI: | 10.1007/s10633-025-10019-0 |
