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'.
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 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!