Feasibility of Automated Segmentation of Pigmented Choroidal Lesions in OCT Data With Deep Learning.
- DOI
- 10.1167/tvst.11.9.25
- Published
- 2022 Sep 1
- Container
- Translational vision science & technology
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1167/tvst.11.9.25,
title = {Feasibility of Automated Segmentation of Pigmented Choroidal Lesions in OCT Data With Deep Learning.},
author = {Valmaggia P and Friedli P and Hörmann B and Kaiser P and Scholl HPN and Cattin PC and Sandkühler R and Maloca PM},
year = {2022},
journal = {Translational vision science \& technology},
doi = {10.1167/tvst.11.9.25},
url = {https://doi.org/10.1167/tvst.11.9.25}
}RIS
TY - JOUR TI - Feasibility of Automated Segmentation of Pigmented Choroidal Lesions in OCT Data With Deep Learning. AU - Valmaggia P AU - Friedli P AU - Hörmann B AU - Kaiser P AU - Scholl HPN AU - Cattin PC AU - Sandkühler R AU - Maloca PM PY - 2022 JO - Translational vision science & technology DO - 10.1167/tvst.11.9.25 UR - https://doi.org/10.1167/tvst.11.9.25 ER -
APA
P, V., P, F., B, H., P, K., HPN, S., PC, C., R, S., & PM, M. (2022). Feasibility of Automated Segmentation of Pigmented Choroidal Lesions in OCT Data With Deep Learning.. Translational vision science & technology. https://doi.org/10.1167/tvst.11.9.25
Source records
- pubmed · retrieved 2026-09-25T04:58:55.687Z
- europe-pmc · retrieved 2026-09-25T04:58:55.724Z