Discovery CORE platform and its AI
BERN, Switzerland, 01 Dec. 08, 2022 (GLOBE NEWSWIRE) — RetinAI Medical AG (“RetinAI”), a leader in the development of software solutions for image processing and artificial intelligence in ophthalmology, is proud to launch Discovery CORE™ with AI for retinal segmentation. fluids and layers. Discovery CORE and its AI models were designed to accelerate data analysis and help clinical and academic researchers collaborate more effectively in real time with their peers on medical and imaging datasets.
The software automatically measures real-time retinal fluid volumes and layer thickness on OCT datasets. Additionally, it incorporates annotation tools and electronic case report forms, which allow for the collection of new data insights across peer networks, keeping information digitized, centralized, and secure. CORE’s functionality can be used to assess disease parameters at scale, initiate the creation of registries and real-world evidence datasets, and help with shared workflows to assess 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 metrics such as fluid volumes and retinal layer thickness on OCT volumes. AI models can be processed on DICOM and other vendor-specific formats for OCT. With the AI model for fluid segmentation, CORE measures subretinal and intraretinal fluid (SRF and IRF) volumes and pigment epithelial detachment (PED). The AI model for layer segmentation measures the total thickness of the retina as well as the layer thickness for 6 individual layers of the retina, including the photoreceptor and the retinal pigment epithelium layer.
Caption: An overview of the Discovery CORE platform and its AI. Features shown include AI overlay on OCT images to visualize fluid and layers, side-by-side imaging comparisons at two different time points or visits, and at the bottom, fluid volume progression plots a patient’s retinal over time.
RetinAI is delighted to offer Discovery CORE and its AI as a free trial for the first 2 months for users who register on the platform. After the free trial, users can subscribe to Discovery CORE and its AI for €179 per month per user to access smooth, layered AI models and other user-friendly features to speed up their analysis and their collaboration on clinical and research datasets. To learn more about Discovery CORE and how to get started, please visit https://www.retinai.com/products/discovery/core.
Launch the webinar
The company is also sponsoring the first in a series of informational webinars titled Improve your research workflows with accelerated data analysis and enhanced collaboration using Discovery CORE™, presented by Prof. Dr. Marion Munk. Professor Munk is a retina specialist and Chief Physician of the University Hospital Bern and Director of the Bern Photographic Reading Center, with extensive experience in clinical and academic research. If you would like to attend this webinar on December 15, 2022 from 7-8 p.m. CET (1-2 p.m. EST), please register here.
RetinAI Medical AG (RetinAI), founded in early 2017, is a Swiss company with offices in Bern and Boston, developing software solutions to accelerate clinical, research and pharmaceutical workflows globally using the machine learning and computer vision. The company builds tools to collect, organize and analyze eye health data, empowering healthcare professionals to make the right healthcare decisions earlier. The international RetinAI team combines clinical, technical and scientific knowledge to support the transition from reactive medicine to preventive medicine for serious eye diseases. www.retinai.com
For more information, please contact:
In the business
RetinAI Medical AG firstname.lastname@example.org
Carlos Ciller, PhD, CEO RetinAI Medical AG email@example.com
Sue Charles, Charles Consultants, firstname.lastname@example.org +44 (0)7968726585
A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/422a7a43-f12e-4252-8143-f96b96ecf280
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