Automated retinal layers segmentation in SD-OCT images using dual-gradient and spatial correlation smoothness constraint.
about
Retinal status analysis method based on feature extraction and quantitative grading in OCT images.The measurement repeatability using different partition methods of intraretinal tomographic thickness maps in healthy human subjects.CuBe: parametric modeling of 3D foveal shape using cubic Bézier.The Edge Detectors Suitable for Retinal OCT Image Segmentation.Retinal Layer Abnormalities as Biomarkers of Schizophrenia.Automated detection of foveal center in SD-OCT images using the saliency of retinal thickness maps.Signal reduction in choriocapillaris and segmentation errors in spectral domain OCT angiography caused by soft drusen.DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images.
P2860
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P2860
Automated retinal layers segmentation in SD-OCT images using dual-gradient and spatial correlation smoothness constraint.
description
2014 nî lūn-bûn
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2014年の論文
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2014年学术文章
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2014年学术文章
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2014年学术文章
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2014年学术文章
@zh-hans
2014年学术文章
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2014年學術文章
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name
Automated retinal layers segme ...... elation smoothness constraint.
@en
Automated retinal layers segme ...... elation smoothness constraint.
@nl
type
label
Automated retinal layers segme ...... elation smoothness constraint.
@en
Automated retinal layers segme ...... elation smoothness constraint.
@nl
prefLabel
Automated retinal layers segme ...... elation smoothness constraint.
@en
Automated retinal layers segme ...... elation smoothness constraint.
@nl
P2093
P1476
Automated retinal layers segme ...... elation smoothness constraint.
@en
P2093
Daniel L Rubin
Luis de Sisternes
Qiang Chen
Weiwei Zhang
P304
P356
10.1016/J.COMPBIOMED.2014.08.028
P50
P577
2014-09-06T00:00:00Z