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Latest press releases

Forbes [FR] | RetinAI, quand l’Intelligence Artificielle détecte et prévient les maladies ophtalmologiques

"Sandro De Zanet, Stefanos Apostolopoulos et Carlos Ciller se sont rencontrés à l’université de Berne où ils faisaient leur doctorat de recherche en traitement d’images, imagerie médicale et machine learning en ophtalmologie…"

AGEFI [FR] | L’examen ophtalmologique facilité par l’intelligence artificielle de RetinAI (FR)

"Nous ne visons pas à remplacer les ophtalmologues. Nous cherchons à rendre leurs tâches et leurs décisions plus aisées», affirme Carlos Ciller, CEO et cofondateur de RetinAI..."

BILAN [FR] | RetinAI soigne les yeux avec l’intelligence artificielle (FR)

" S’il est un domaine où l’intelligence artificielle a fait ses preuves récemment, c’est bien dans la reconnaissance d’images, y compris médicales, pour l’aide au diagnostic... "

Unternehmer Zeitung - UZ [DE]

An der letzten Session des Jahres in Lausanne haben RetinAI und Skypull das Finale von Venture Kick gewonnen und sich damit je 130'000 Franken gesichert (DE)

Latest updates

Machine learning can predict anti-VEGF treatment demand in a Treat-and-Extend regimen for patients with nAMD, DME and RVO associated ME

2 new Posters in ARVO 2021 Virtual

We are very excited of our team and collaborators presenting 2 posters in ARVO 2021! One Poster on 'Longitudinal analysis of Retinal Pigment Epithelium Atrophy progression using an automated segmentation algorithm' providing segmentation analysis over 5 years using deep learning,
and a poster on 'Automated fovea and optic disc detection in the presence of occlusions in Fundus SLO Images'.

New publication on TVST - Automated quantification of pathological fluids in neovascular age-related degeneration, and it's repeatability using deep learning

In this peer reviewed publication, we develop a reliable algorithm for the automated identification, localization, and volume measurement of exudative manifestations in neovascular age-related macular degeneration (nAMD), including intraretinal (IRF), subretinal fluid (SRF), and pigment epithelium detachment (PED), using a deep-learning approach. The deep-learning algorithm can simultaneously acquire a high level of performance for the identification and volume measurements of IRF, SRF, and PED in nAMD, providing accurate and repeatable predictions. Including layer segmentation during training and squeeze-excite block in the network architecture were shown to boost the performance. Source: Mantel et al. , TVST 2021, 10 (17) - https://doi.org/10.1167/tvst.10.4.17 Authors: Irmela Mantel; Agata Mosinska; Ciara Bergin; Maria Sole Polito; Jacopo Guidotti; Stefanos Apostolopoulos; Carlos Ciller; Sandro De Zanet

Translation Vision Science and Technology

RetinAI receives ISO 13485:2016 certification

Retinai has just received the ISO 13485 certification, a recognition awarded by regulatory bodies and necessary for companies willing to develop & commercialise Medical Devices. RetinAI Discovery, our platform for medical image and data management in ophthalmology, is now getting ready to be commercialised to clinics as a medical device. We are extremely proud of the team for achieving the certification!

Contact us for more informations! We are happy to hear from you!