TY - JOUR
T1 - Brain-inspired algorithms for retinal image analysis
AU - ter Haar Romeny, B.M.
AU - Bekkers, E.J.
AU - Zhang, J.
AU - Abbasi-Sureshjani, S.
AU - Huang, F.
AU - Duits, R.
AU - Dasht Bozorg, Behdad
AU - Berendschot, T.T.J.M.
AU - Smit-Ockeloen, I.
AU - Eppenhof, K.A.J.
AU - Feng, J.
AU - Hannink, J.
AU - Schouten, J.
AU - Tong, M.
AU - Wu, H.
AU - van Triest, J.W.
AU - Zhu, S.
AU - Chen, D.
AU - He, W.
AU - Xu, L.
AU - Han, P.
AU - Kang, Y.
PY - 2016/11
Y1 - 2016/11
N2 - 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.
AB - 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.
KW - Diabetic retinopathy
KW - Multi-orientation
KW - Orientation scores
KW - Retina
KW - Screening
KW - SE(2)
KW - Tortuosity
KW - Vessel analysis
UR - http://www.scopus.com/inward/record.url?scp=84975110691&partnerID=8YFLogxK
U2 - 10.1007/s00138-016-0771-9
DO - 10.1007/s00138-016-0771-9
M3 - Article
AN - SCOPUS:84975110691
SN - 0932-8092
VL - 27
SP - 1117
EP - 1135
JO - Machine Vision and Applications
JF - Machine Vision and Applications
IS - 8
ER -
