Automated Ultrasound Technology to Diagnose Traumatic Retinal Detachment
Abstract
Our objective is to develop and validate a prototype mobile AI-enabled software platform that can accurately detect sonographic signs of retinal detachment and support a regulatory filing with the Food and Drug Administration. Our goal is to make the deep-learning ultrasound algorithms commercially available for use in the clinical environment to rapidly detect retinal detachment along with the status of macula to direct appropriate therapy. We hypothesized that machine learning algorithms will be reproducible and will have accurate diagnostic capability to detect findings specific to retinal detachment and macular involvement on ultrasound images. To date, we have successfully extracted, labeled, and curated the ocular image datasets. The training dataset has been utilized to train the algorithm, with the initial focus on learning normal ocular sonographic anatomy. Our next steps will involve refining the architecture of the developed network to achieve the best fit for the distribution and validation.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 2023
- Accession Number
- AD1216445
Entities
People
- Srikar Adhikari
Organizations
- University of Arizona