title: Automated Segmentability Index for Layer Segmentation of Macular SD-OCT Images.
abstract: OBJECTIVE
  To automatically identify which spectral-domain optical coherence tomography (SD-OCT) scans will provide reliable automated layer segmentations for more accurate layer thickness analyses in population studies.
  
  
  METHODS
  Six hundred ninety macular SD-OCT image volumes (6.0 × 6.0 × 2.3 mm3) were obtained from one eyes of 690 subjects (74.6 ± 9.7 [mean ± SD] years, 37.8% of males) randomly selected from the population-based Rotterdam Study. The dataset consisted of 420 OCT volumes with successful automated retinal nerve fiber layer (RNFL) segmentations obtained from our previously reported graph-based segmentation method and 270 volumes with failed segmentations. To evaluate the reliability of the layer segmentations, we have developed a new metric, segmentability index SI, which is obtained from a random forest regressor based on 12 features using OCT voxel intensities, edge-based costs, and on-surface costs. The SI was compared with well-known quality indices, quality index (QI), and maximum tissue contrast index (mTCI), using receiver operating characteristic (ROC) analysis.
  
  
  RESULTS
  The 95% confidence interval (CI) and the area under the curve (AUC) for the QI are 0.621 to 0.805 with AUC 0.713, for the mTCI 0.673 to 0.838 with AUC 0.756, and for the SI 0.784 to 0.920 with AUC 0.852. The SI AUC is significantly larger than either the QI or mTCI AUC (P< 0.01).
  
  
  CONCLUSIONS
  The segmentability index SI is well suited to identify SD-OCT scans for which successful automated intraretinal layer segmentations can be expected.
  
  
  CONCLUSIONS
  Interpreting the quantification of SD-OCT images requires the underlying segmentation to be reliable, but standard SD-OCT quality metrics do not predict which segmentations are reliable and which are not. The segmentability index SI presented in this study does allow reliable segmentations to be identified, which is important for more accurate layer thickness analyses in research and population studies.
authors.affiliation: Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA ; Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, IA, USA.
authors.forename: Kyungmoo
authors.initials: K
authors.lastname: Lee
authors.affiliation: Department of Ophthalmology, Erasmus Medical Center, Rotterdam, the Netherlands ; Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands.
authors.forename: Gabriëlle H S
authors.initials: GH
authors.lastname: Buitendijk
authors.affiliation: Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA ; Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, IA, USA.
authors.forename: Hrvoje
authors.initials: H
authors.lastname: Bogunovic
authors.affiliation: Department of Ophthalmology, Erasmus Medical Center, Rotterdam, the Netherlands ; Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands.
authors.forename: Henriët
authors.initials: H
authors.lastname: Springelkamp
authors.affiliation: Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands ; Netherlands Consortium for Healthy Aging, Netherlands Genomics Initiative, the Hague, the Netherlands.
authors.forename: Albert
authors.initials: A
authors.lastname: Hofman
authors.affiliation: Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA ; Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, IA, USA.
authors.forename: Andreas
authors.initials: A
authors.lastname: Wahle
authors.affiliation: Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA ; Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, IA, USA ; Department of Ophthalmology and Visual Sciences, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
authors.forename: Milan
authors.initials: M
authors.lastname: Sonka
authors.affiliation: Department of Ophthalmology, Erasmus Medical Center, Rotterdam, the Netherlands ; Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands.
authors.forename: Johannes R
authors.initials: JR
authors.lastname: Vingerling
authors.affiliation: Department of Ophthalmology, Erasmus Medical Center, Rotterdam, the Netherlands ; Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands.
authors.forename: Caroline C W
authors.initials: CC
authors.lastname: Klaver
authors.affiliation: Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA ; Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, IA, USA ; Department of Ophthalmology and Visual Sciences, University of Iowa Hospitals and Clinics, Iowa City, IA, USA ; Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA ; Stephen A. Wynn Institute for Vision Research, University of Iowa, Iowa City, IA, USA ; Department of Veterans Affairs, Iowa City VA Medical Center, Iowa City, IA, USA.
authors.forename: Michael D
authors.initials: MD
authors.lastname: Abràmoff
keywords: image quality; intraretinal layer segmentation; retinal nerve fiber layer; segmentability index; spectral-domain optical coherence tomography