2019
DOI: 10.1038/s41598-019-48368-x
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Publisher Correction: Automatic Choroid Layer Segmentation from Optical Coherence Tomography Images Using Deep Learning

Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Cited by 4 publications
(1 citation statement)
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“…The latest technologies allow non-invasive imaging, along with the qualitative and quantitative in vivo assessment of the human choroid [ 13 ]. At present, most ophthalmologists manually define the boundaries of the choroid to measure its thickness; however, some studies have introduced different automatic choroidal segmentation methods [ 14 , 15 , 16 ]. The choroidal vasculature has been broadly investigated in humans.…”
Section: Introductionmentioning
confidence: 99%
“…The latest technologies allow non-invasive imaging, along with the qualitative and quantitative in vivo assessment of the human choroid [ 13 ]. At present, most ophthalmologists manually define the boundaries of the choroid to measure its thickness; however, some studies have introduced different automatic choroidal segmentation methods [ 14 , 15 , 16 ]. The choroidal vasculature has been broadly investigated in humans.…”
Section: Introductionmentioning
confidence: 99%