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Brain-inspired algorithms for retinal image analysis.
- Source :
- Machine Vision & Applications; Nov2016, Vol. 27 Issue 8, p1117-1135, 19p
- Publication Year :
- 2016
-
Abstract
- Retinal image analysis is a challenging problem due to the precise quantification required and the huge numbers of images produced in screening programs. This paper describes a series of innovative brain-inspired algorithms for automated retinal image analysis, recently developed for the RetinaCheck project, a large-scale screening program for diabetic retinopathy and other retinal diseases in Northeast China. The paper discusses the theory of orientation scores, inspired by cortical multi-orientation pinwheel structures, and presents applications for automated quality assessment, optic nerve head detection, crossing-preserving enhancement and segmentation of retinal vasculature, arterio-venous ratio, fractal dimension, and vessel tortuosity and bifurcations. Many of these algorithms outperform state-of-the-art techniques. The methods are currently validated in collaborating hospitals, with a rich accompanying base of metadata, to phenotype and validate the quantitative algorithms for optimal classification power. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09328092
- Volume :
- 27
- Issue :
- 8
- Database :
- Complementary Index
- Journal :
- Machine Vision & Applications
- Publication Type :
- Academic Journal
- Accession number :
- 119974274
- Full Text :
- https://doi.org/10.1007/s00138-016-0771-9