title: Elliptical local vessel density: a fast and robust quality metric for retinal images.
abstract: A great effort of the research community is geared towards the creation of an automatic screening system able to promptly detect diabetic retinopathy with the use of fundus cameras. In addition, there are some documented approaches for automatically judging the image quality. We propose a new set of features independent of field of view or resolution to describe the morphology of the patient's vessels. Our initial results suggest that these features can be used to estimate the image quality in a time one order of magnitude shorter than previous techniques.
authors.affiliation: European VIBOT program, France. giancardol@ornl.gov
authors.forename: L
authors.initials: L
authors.lastname: Giancardo
authors.forename: M D
authors.initials: MD
authors.lastname: Abramoff
authors.forename: E
authors.initials: E
authors.lastname: Chaum
authors.forename: T P
authors.initials: TP
authors.lastname: Karnowski
authors.forename: F
authors.initials: F
authors.lastname: Meriaudeau
authors.forename: K W
authors.initials: KW
authors.lastname: Tobin
mesh_terms: D000465:Algorithms; D001331:Automation; D003930:Diabetic Retinopathy / Q000175:diagnosis* / Q000473:pathology*; D001330:Electronic Data Processing; D006801:Humans; D007089:Image Enhancement; D015233:Models, Statistical; D009898:Optic Disk / Q000033:anatomy & histology / Q000473:pathology*; D015203:Reproducibility of Results; D012160:Retina / Q000033:anatomy & histology* / Q000473:pathology; D012164:Retinal Diseases / Q000175:diagnosis*; D012171:Retinal Vessels / Q000473:pathology; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors