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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.
Highlights
Diabetes is reaching epidemic proportions worldwide, especially in Asia due to fast lifestyle changes and genetic factors
Better performance is obtained by including contextual information, e.g., by incorporating the characteristic pattern of large blood vessel arches in the upper and lower retina emerging from the ONH [45,46,64], but this comes at higher computational costs
We have developed a fully automatic bifurcation and crossing detection algorithm called Biologically Inspired CRossing detecting in Orientation Scores (BICROS) [55], see Fig. 11, which does not depend on vessel segmentations
Summary
Diabetes is reaching epidemic proportions worldwide, especially in Asia due to fast lifestyle changes and genetic factors. To set up a screening program for the detection of early signs of diabetic retinopathy (DR), glaucoma and age-related macula degeneration (AMD), a Sino-Dutch consortium was formed and the project RetinaCheck was defined with the following four phases: (1) development of innovative algorithms for automated and quantitative detection of relevant bio-markers, (2) set up a significant validation study correlating the imaging data with relevant clinical metadata, and (3) roll out a screening infrastructure in the province of Liaoning, Northeast China, and (4) make a sustainable commercial infrastructure. Several other early DR signs can be measured, such as nerve damage in the cornea with confocal laser microscopy, or changes in retina neural tissue layer thickness with optical coherence tomography (OCT), but these methods are more costly and more labor intensive, especially given the projected huge-scale screening and the much lower availability of OCT in China.
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