Automated image processing pipeline for adaptive optics scanning light ophthalmoscopy
Biomedical Optics Express, ISSN: 2156-7085, Vol: 12, Issue: 6, Page: 3142-3168
2021
- 9Citations
- 9Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations9
- Citation Indexes9
- CrossRef8
- Captures9
- Readers9
Article Description
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.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85106351305&origin=inward; http://dx.doi.org/10.1364/boe.418079; http://www.ncbi.nlm.nih.gov/pubmed/34221651; https://opg.optica.org/abstract.cfm?URI=boe-12-6-3142; https://dx.doi.org/10.1364/boe.418079; https://opg.optica.org/boe/fulltext.cfm?uri=boe-12-6-3142&id=450858
Optica Publishing Group
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know