title: Three-dimensional spectral-domain optical coherence tomography data analysis for glaucoma detection.
abstract: OBJECTIVE
  To develop a new three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) data analysis method using a machine learning technique based on variable-size super pixel segmentation that efficiently utilizes full 3D dataset to improve the discrimination between early glaucomatous and healthy eyes.
  
  
  METHODS
  192 eyes of 96 subjects (44 healthy, 59 glaucoma suspect and 89 glaucomatous eyes) were scanned with SD-OCT. Each SD-OCT cube dataset was first converted into 2D feature map based on retinal nerve fiber layer (RNFL) segmentation and then divided into various number of super pixels. Unlike the conventional super pixel having a fixed number of points, this newly developed variable-size super pixel is defined as a cluster of homogeneous adjacent pixels with variable size, shape and number. Features of super pixel map were extracted and used as inputs to machine classifier (LogitBoost adaptive boosting) to automatically identify diseased eyes. For discriminating performance assessment, area under the curve (AUC) of the receiver operating characteristics of the machine classifier outputs were compared with the conventional circumpapillary RNFL (cpRNFL) thickness measurements.
  
  
  RESULTS
  The super pixel analysis showed statistically significantly higher AUC than the cpRNFL (0.855 vs. 0.707, respectively, p = 0.031, Jackknife test) when glaucoma suspects were discriminated from healthy, while no significant difference was found when confirmed glaucoma eyes were discriminated from healthy eyes.
  
  
  CONCLUSIONS
  A novel 3D OCT analysis technique performed at least as well as the cpRNFL in glaucoma discrimination and even better at glaucoma suspect discrimination. This new method has the potential to improve early detection of glaucomatous damage.
authors: University of Pittsburgh Medical Center Eye Center, Eye and Ear Institute, Ophthalmology and Visual Science Research Center, Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
authors: Juan
authors: J
authors: Xu
authors: Hiroshi
authors: H
authors: Ishikawa
authors: Gadi
authors: G
authors: Wollstein
authors: Richard A
authors: RA
authors: Bilonick
authors: Lindsey S
authors: LS
authors: Folio
authors: Zach
authors: Z
authors: Nadler
authors: Larry
authors: L
authors: Kagemann
authors: Joel S
authors: JS
authors: Schuman
mesh_terms: D016022:Case-Control Studies; D005901:Glaucoma / Q000175:diagnosis*; D006801:Humans; D041623:Tomography, Optical Coherence / Q000379:methods*