Unsupervised identification of cone photoreceptors in non-confocal adaptive optics scanning light ophthalmoscope images.
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Photoreceptor-Based Biomarkers in AOSLO Retinal Imaging.Use of focus measure operators for characterization of flood illumination adaptive optics ophthalmoscopy image quality.Automatic Cone Photoreceptor Localisation in Healthy and Stargardt Afflicted Retinas Using Deep Learning.The Reliability of Cone Density Measurements in the Presence of Rods.Cone Photoreceptor Cell Segmentation and Diameter Measurement on Adaptive Optics Images Using Circularly Constrained Active Contour ModelDeep learning based detection of cone photoreceptors with multimodal adaptive optics scanning light ophthalmoscope images of achromatopsia
P2860
Unsupervised identification of cone photoreceptors in non-confocal adaptive optics scanning light ophthalmoscope images.
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2017 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2017 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2017年の論文
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2017年論文
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2017年論文
@zh-hant
2017年論文
@zh-hk
2017年論文
@zh-mo
2017年論文
@zh-tw
2017年论文
@wuu
name
Unsupervised identification of ...... g light ophthalmoscope images.
@ast
Unsupervised identification of ...... g light ophthalmoscope images.
@en
type
label
Unsupervised identification of ...... g light ophthalmoscope images.
@ast
Unsupervised identification of ...... g light ophthalmoscope images.
@en
prefLabel
Unsupervised identification of ...... g light ophthalmoscope images.
@ast
Unsupervised identification of ...... g light ophthalmoscope images.
@en
P2093
P2860
P50
P356
P1476
Unsupervised identification of ...... g light ophthalmoscope images.
@en
P2093
Adam M Dubis
Benjamin Davidson
Joseph Carroll
Melissa Kasilian
Michel Michaelides
P2860
P304
P356
10.1364/BOE.8.003081
P577
2017-05-26T00:00:00Z