title: A novel computer aided quantification method of focal arteriolar narrowing using colour retinal image.
abstract: We present a novel method for the quantification of focal arteriolar narrowing (FAN) in human retina, a precursor for hypertension, stroke and other cardiovascular diseases. A reliable and robust arteriolar boundary mapping method is proposed where intensity, gradient and spatial prior knowledge about the arteriolar shape is incorporated into a graph based optimization method to obtain the arteriolar boundary. Following the mapping of the arteriolar boundaries, arteriolar widths are analysed to quantify the severity of focal arteriolar narrowing (FAN). We evaluate our proposed method on a dataset of 116 retinal arteriolar segments which are manually graded by two expert graders. The experimental results indicate a strong correlation between the quantified FAN measurement scores provided by our method and two experts graded FAN severity levels. Our proposed FAN measurement score: percent narrowing (PN) shows high correlation (Spearman correlation coefficient of 0.82(p<0.0001) for grader-1 and 0.84(p<0.0001) for grade-2) with the manually graded FAN severity levels provided by two expert graders. In addition to that, the proposed method shows better reproducibility (Spearman correlation coefficient ρ=0.92(p<0.0001)) compared to two expert graders ( [Formula: see text] (p<0.0001) and [Formula: see text] ) in two successive sessions. The quantitative measurements provided by the proposed method can help us to establish a more reliable link between FAN and known systemic and eye diseases.
authors.affiliation: Department of Computing and Information Systems, The University of Melbourne, Australia. Electronic address: royp@student.unimelb.edu.au.
authors.forename: Pallab Kanti
authors.initials: PK
authors.lastname: Roy
authors.affiliation: Department of Computing and Information Systems, The University of Melbourne, Australia.
authors.forename: Alauddin
authors.initials: A
authors.lastname: Bhuiyan
authors.affiliation: Centre for Eye Research Australia, Melbourne, Australia.
authors.forename: Kim
authors.initials: K
authors.lastname: Lee
authors.affiliation: Department of Ophthalmology, National University of Singapore, Singapore.
authors.forename: Tien Yin
authors.initials: TY
authors.lastname: Wong
authors.affiliation: Department of Computing and Information Systems, The University of Melbourne, Australia.
authors.forename: Kotagiri
authors.initials: K
authors.lastname: Ramamohanarao
mesh_terms: D005260:Female; D006801:Humans; D006973:Hypertension / Q000000981:diagnostic imaging* / Q000503:physiopathology; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D012161:Retinal Artery / Q000000981:diagnostic imaging* / Q000503:physiopathology
keywords: Artery; Focal arteriolar narrowing assessment crossover detection; Retinal image; Vein; Vessel width measurement