RetinAI Launches Discovery CORE: AI Platform for Retinal Fluid and Layer Segmentation

RetinAI Medical AG has launched Discovery CORE with AI for retinal fluid and layer segmentation. Discovery CORE and its AI models have been designed to accelerate data analysis and help clinical and academic researchers collaborate more efficiently in real time with their peers on medical and imaging datasets.

The software measures retinal fluid volumes and layer thickness across OCT datasets automatically in real time. Further, it integrates annotation tools and electronic case report forms, which enable new data insights to be collected across peer networks, keeping the information digitized, centralized and secure, according to a company news release. The functionality of CORE can be used to assess disease endpoints at scale, jump-start the building of registries and real-world evidence datasets, and help with shared workflows to evaluate data, train physicians and establish best practices within the clinic.

Discovery CORE uses RetinAI’s CE-marked fluid and layer segmentation AI models to quickly visualize and generate measures such as fluid volumes and retinal layer thickness on OCT volumes. The AI models can be processed on DICOM and other vendor-specific formats for OCT. With the AI model for fluid segmentation, CORE measures volumes for subretinal and intraretinal fluid (SRF and IRF), and pigment epithelium detachment (PED). The AI model for layer segmentation measures total retinal thickness as well as layer thickness for 6 individual layers of the retina, including the photoreceptor and retinal pigment epithelium layer.

The company is also sponsoring the first of a series of informational webinars titled Elevate your research workflows with accelerated data analysis and improved collaboration using Discovery CORE, presented by Prof. Dr. Marion Munk. Prof. Dr. Munk is a Retina Specialist and Senior Physician of the University of Bern Hospital and the Managing Director of the Bern Photographic Reading Center, with extensive experience in clinical and academic research. If you are interested in participating in this webinar on December 15, 2022 from 7pm-8pm CET (1pm-2pm EST), register here.