Retinal vascular tree morphology: a semi-automatic quantification

By M. Elena Martínez-Pérez, Alun D. Hughes, A. Stanton, Simon A. Thom, N. Chapman, Anil Anthony Bharath, Kim H. Parker. IEEE Transactions on Biomedical Engineering, 2002

295 citations recorded by the source corpus.

Subfields: Ophthalmology, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/c7c978e4f3489614d59be2e46c76b7e831da93e6

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In Ophthalmology

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

2007 Guidelines for the Management of Arterial Hypertension: The Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC) (2007, methodology): “More selective methods for objectively investigating ocular damage in hypertension have been developed and studied.(260) For instance, digitized retinal photographs can be analysed by a semiautomated program to quantify geometric and topological properties of arteriolar and venular tree.”
2007 ESH‐ESC Guidelines for the management of arterial hypertension (2007, background): “(260) For instance, digitized retinal photographs can be analysed by a semiautomated program to quantify geometric and topological properties of arteriolar and venular tree.”
Segmentation of blood vessels from red-free and fluorescein retinal images (2007, methodology): “…lengths, tortuosity, length to diameter ratios, etc. (Gelman et al., 2005) and network properties such as connectivity, branch ordering, purely topological indices which describe the shape of branching trees (Martinez-Perez et al., 2002; Hughes et al., 2006), and if appropriate, fractal properties.”
Blood vessel segmentation methodologies in retinal images - A survey (2012, unknown): “the RISA system [95].”
Image-Based Phenotyping of the Mature Arabidopsis Shoot System (2014, background): “It already exists a great amount of different approaches [12,20,24,33–35] for the automated segmentation or skeleton extraction, the amount of approaches for labeling and grouping of trees or sub-trees inside these networks is rather limited [5,17,18,21,30].”
Retinal Blood Vessel Segmentation Using Line Operators and Support Vector Classification (2007, background): “the skeleton and the branching points [3].”
Fast Retinal Vessel Detection and Measurement Using Wavelets and Edge Location Refinement (2012, background): “Two notable exceptions are ‘Vessel Finder’ [27] and ‘Retinal Image multiScale Analysis’ (RISA) [28], both of which have been applied to the analysis of retinal images of infants at risk of retinopathy of prematurity (ROP).”