Automated image processing pipeline for adaptive optics scanning light ophthalmoscopy. Biomed Opt Express 2021 Jun 01;12(6):3142-3168
Date
07/06/2021Pubmed ID
34221651Pubmed Central ID
PMC8221964DOI
10.1364/BOE.418079Scopus ID
2-s2.0-85106351305 (requires institutional sign-in at Scopus site) 5 CitationsAbstract
To mitigate the substantial post-processing burden associated with adaptive optics scanning light ophthalmoscopy (AOSLO), we have developed an open-source, automated AOSLO image processing pipeline with both "live" and "full" modes. The live mode provides feedback during acquisition, while the full mode is intended to automatically integrate the copious disparate modules currently used in generating analyzable montages. The mean (±SD) lag between initiation and montage placement for the live pipeline was 54.6 ± 32.7s. The full pipeline reduced overall human operator time by 54.9 ± 28.4%, with no significant difference in resultant cone density metrics. The reduced overhead decreases both the technical burden and operating cost of AOSLO imaging, increasing overall clinical accessibility.
Author List
Salmon AE, Cooper RF, Chen M, Higgins B, Cava JA, Chen N, Follett HM, Gaffney M, Heitkotter H, Heffernan E, Schmidt TG, Carroll JAuthors
Joseph J. Carroll PhD Director, Professor in the Ophthalmology and Visual Sciences department at Medical College of WisconsinRobert F. Cooper Ph.D Assistant Professor in the Biomedical Engineering department at Marquette University
Taly Gilat-Schmidt PhD Associate Professor of Biomedical Engineering in the Biomedical Engineering department at Marquette University
