title: Automated analysis of differential interference contrast microscopy images of the foveal cone mosaic.
abstract: An algorithm is presented for processing and analysis of differential interference contrast (DIC) microscopy images of the fovea to study the cone mosaic. The algorithm automatically locates the cones and their boundaries in such images and is assessed by comparison with results from manual analysis. Additional algorithms are presented that analyze the cone positions to extract information on cone neighbor relationships as well as the short-range order and domain structure of the mosaic. The methods are applied to DIC images of the human fovea.
authors.affiliation: Computational Imaging Group, Department of Electrical and Computer Engineering, University of Canterbury, Christchurch, New Zealand.
authors.forename: David H
authors.initials: DH
authors.lastname: Wojtas
authors.forename: Bing
authors.initials: B
authors.lastname: Wu
authors.forename: Peter K
authors.initials: PK
authors.lastname: Ahnelt
authors.forename: Philip J
authors.initials: PJ
authors.lastname: Bones
authors.forename: R P
authors.initials: RP
authors.lastname: Millane
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D005584:Fovea Centralis / Q000166:cytology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008857:Microscopy, Interference / Q000379:methods*; D009887:Ophthalmoscopy / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D017949:Retinal Cone Photoreceptor Cells / Q000166:cytology*; D012680:Sensitivity and Specificity