This research aims to identify effective biomarkers for early detection of retinal vein occlusion (RVO) changes.
Applied geometric decomposition of density into length and diameter.
Analyzed OCT angiography data from RVO patients.
Compared congestive and compensatory phenotypes.
Identified length and diameter as superior biomarkers for detecting changes.
Found that the proposed method effectively monitors congestive status in RVO eyes.
Revealed distinct patterns between congestive and compensatory phenotypes.
Abstract
Decomposing density into length and diameter provides superior biomarkers for detecting early subclinical changes and monitoring the congestive status of RVO eyes.