title: Novel fractal feature-based multiclass glaucoma detection and progression prediction.
abstract: We investigate the use of fractal analysis (FA) as the basis of a system for multiclass prediction of the progression of glaucoma. FA is applied to pseudo two-dimensional images converted from one-dimensional retinal nerve fiber layer (RNFL) data obtained from the eyes of normal subjects, and from subjects with progressive and non-progressive glaucoma. FA features are obtained using a box-counting method and a multi-fractional Brownian motion method that incorporates texture and multiresolution analyses. Both features are used for Gaussian kernel-based multiclass classification. Sensitivity, specificity, and area under receiver operating characteristic curve (AUROC) are computed for the FA features and for metrics obtained using wavelet-Fourier analysis (WFA) and fast-Fourier analysis (FFA). The AUROCs that predict progressors from non-progressors based on classifiers trained using a dataset comprised of non-progressors and ocular normal subjects are 0.70, 0.71 and 0.82 for WFA, FFA, and FA, respectively. The correct multiclass classification rates among progressors, non-progressors, and ocular normal subjects are 0.82, 0.86 and 0.88 for WFA, FFA, and FA, respectively. Simultaneous multiclass classification among progressors, non-progressors, and ocular normal subjects has not been previously described. The novel FA-based features achieve better performance with fewer features and less computational complexity than WFA and FFA.
authors.forename: Paul Y
authors.initials: PY
authors.lastname: Kim
authors.forename: Khan M
authors.initials: KM
authors.lastname: Iftekharuddin
authors.forename: Pinakin G
authors.initials: PG
authors.lastname: Davey
authors.forename: Márta
authors.initials: M
authors.lastname: Tóth
authors.forename: Anita
authors.initials: A
authors.lastname: Garas
authors.forename: Gabor
authors.initials: G
authors.lastname: Holló
authors.forename: Edward A
authors.initials: EA
authors.lastname: Essock
mesh_terms: D000465:Algorithms; D019540:Area Under Curve; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003941:Diagnostic Techniques, Ophthalmological; D018450:Disease Progression; D005583:Fourier Analysis; D017709:Fractals; D005901:Glaucoma / Q000175:diagnosis* / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016571:Neural Networks, Computer; D012372:ROC Curve; D012160:Retina