Retinal Vessel Segmentation Using A New Topological Method

08/03/2016

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A novel topological segmentation of retinal images represents blood vessels as connected regions in the continuous image plane, having shape-related analytic and geometric properties. This paper presents topological segmentation results from the DRIVE retinal image database.

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Retinal Vessel Segmentation Using A New Topological Method

A Trio-Method for Retinal Vessel Segmentation using Image Processing

Automatic Segmentation of Retinal Vasculature

A Hierarchical Image Matting Model for Blood Vessel Segmentation in Fundus images

Human Recognition based on Retinal Bifurcations and Modified Correlation Function

Topological Similarity Index and Loss Function for Blood Vessel Segmentation

PixelBNN: Augmenting the PixelCNN with batch normalization and the presentation of a fast architecture for retinal vessel segmentation

PVBM: A Python Vasculature Biomarker Toolbox Based On Retinal Blood Vessel Segmentation

Retinal Vessel Segmentation Using A New Topological Method

Related Research

A Trio-Method for Retinal Vessel Segmentation using Image Processing

Automatic Segmentation of Retinal Vasculature

A Hierarchical Image Matting Model for Blood Vessel Segmentation in Fundus images

Human Recognition based on Retinal Bifurcations and Modified Correlation Function

Topological Similarity Index and Loss Function for Blood Vessel Segmentation

PixelBNN: Augmenting the PixelCNN with batch normalization and the presentation of a fast architecture for retinal vessel segmentation

PVBM: A Python Vasculature Biomarker Toolbox Based On Retinal Blood Vessel Segmentation