about
A review on automatic analysis techniques for color fundus photographsAnalysis of normal human retinal vascular network architecture using multifractal geometryAutomated identification of retinal vessels using a multiscale directional contrast quantification (MDCQ) strategy.Retinal vessel segmentation: an efficient graph cut approach with retinex and local phaseRegional Image Features Model for Automatic Classification between Normal and Glaucoma in Fundus and Scanning Laser Ophthalmoscopy (SLO) Images.A framework for retinal vasculature segmentation based on matched filters.Characterization of human retinal vessel arborisation in normal and amblyopic eyes using multifractal analysisReal-Time Retinal Vessel Mapping and Localization for Intraocular SurgeryRobust Retinal Blood Vessel Segmentation Based on Reinforcement Local DescriptionsAutomated analysis of diabetic retinopathy images: principles, recent developments, and emerging trends.Delineation of blood vessels in pediatric retinal images using decision trees-based ensemble classification.Multi-level deep supervised networks for retinal vessel segmentation.A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region Based Otsu Thresholding.Application of morphological bit planes in retinal blood vessel extraction.Characterisation of human non-proliferative diabetic retinopathy using the fractal analysis.Similarity regularized sparse group lasso for cup to disc ratio computation.Retinal vessel detection and measurement for computer-aided medical diagnosisComparative study of retinal vessel segmentation based on global thresholding techniques.Segmentation of perivascular spaces in 7T MR image using auto-context model with orientation-normalized features.A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis.Supervised retinal vessel segmentation from color fundus images based on matched filtering and AdaBoost classifier.Perivascular Spaces Segmentation in Brain MRI Using Optimal 3D Filtering.Selective Search and Intensity Context Based Retina Vessel Image Segmentation.Retinal blood vessel segmentation with neural network by using gray-level co-occurrence matrix-based features.An improved retinal vessel segmentation method based on high level features for pathological images.Superpixel-Based Line Operator for Retinal Blood Vessel SegmentationRetinal Vessel Segmentation: A Comparative Study of Fuzzy C-Means and Sum Entropy Information on Phase Congruency
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description
2010 nî lūn-bûn
@nan
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
2010年论文
@zh
2010年论文
@zh-cn
name
FABC: retinal vessel segmentation using AdaBoost.
@en
FABC: retinal vessel segmentation using AdaBoost.
@nl
type
label
FABC: retinal vessel segmentation using AdaBoost.
@en
FABC: retinal vessel segmentation using AdaBoost.
@nl
prefLabel
FABC: retinal vessel segmentation using AdaBoost.
@en
FABC: retinal vessel segmentation using AdaBoost.
@nl
P1476
FABC: retinal vessel segmentation using AdaBoost
@en
P2093
Carmen Alina Lupascu
P304
P356
10.1109/TITB.2010.2052282
P577
2010-06-07T00:00:00Z