title: [Algorithm of locally adaptive region growing based on multi-template matching applied to automated detection of hemorrhages].
abstract: In order to automatically detect hemorrhages in fundus images, and develop an automated diabetic retinopathy screening system, a novel algorithm named locally adaptive region growing based on multi-template matching was established and studied. Firstly, spectral signature of major anatomical structures in fundus was studied, so that the right channel among RGB channels could be selected for different segmentation objects. Secondly, the fundus image was preprocessed by means of HSV brightness correction and contrast limited adaptive histogram equalization (CLAHE). Then, seeds of region growing were founded out by removing optic disc and vessel from the resulting image of normalized cross-correlation (NCC) template matching on the previous preprocessed image with several templates. Finally, locally adaptive region growing segmentation was used to find out the exact contours of hemorrhages, and the automated detection of the lesions was accomplished. The approach was tested on 90 different resolution fundus images with variable color, brightness and quality. Results suggest that the approach could fast and effectively detect hemorrhages in fundus images, and it is stable and robust. As a result, the approach can meet the clinical demands.
authors.affiliation: College of Mechanical & Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. gww03020234@sina.com
authors.forename: Wei-Wei
authors.initials: WW
authors.lastname: Gao
authors.forename: Jian-Xin
authors.initials: JX
authors.lastname: Shen
authors.forename: Yu-Liang
authors.initials: YL
authors.lastname: Wang
authors.forename: Chun
authors.initials: C
authors.lastname: Liang
authors.forename: Jing
authors.initials: J
authors.lastname: Zuo
mesh_terms: D000465:Algorithms; D003930:Diabetic Retinopathy / Q000175:diagnosis*; D005654:Fundus Oculi; D006801:Humans; D007091:Image Processing, Computer-Assisted; D010781:Photography; D012166:Retinal Hemorrhage / Q000175:diagnosis*