Abstract

The development and implementation of an intelligent system for automatic image description of an optical coherence tomograph allows us to reduce the time of image processing and, consequently, to accelerate the diagnosis of diseases. To develop this system, it is necessary to solve many problems of binary classification for the presence of markers characterizing pathologies of various types or their absence. In this regard, this work is aimed at developing models that effectively solve many problems of binary classification of optical coherence tomography (OCT) images to describe the state of the retina.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.