We are thrilled to see the results of our latest collaboration with the Augenklinik at Inselspital and the AIMI lab at the ARTORG Center for Biomedical Engineering Research in Ophthalmology Retina!
Machine learning can predict anti-VEGF treatment demand in a Treat-and-Extend regimen for patients with nAMD, DME and RVO associated ME.
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!