title: 4D Graph-Based Segmentation for Reproducible and Sensitive Choroid Quantification From Longitudinal OCT Scans.
abstract: Longitudinal imaging is becoming more commonplace for studies of disease progression, response to treatment, and healthy maturation. Accurate and reproducible quantification methods are desirable to fully mine the wealth of data in such datasets. However, most current retinal OCT segmentation methods are cross-sectional and fail to leverage the inherent context present in longitudinal sequences of images.
  
  
  
  We propose a novel graph-based method for segmentation of multiple three-dimensional (3D) scans over time (termed 3D + time or 4D). The usefulness of this approach in retinal imaging is illustrated in the segmentation of the choroidal surfaces from longitudinal optical coherence tomography (OCT) scans. A total of 3219 synthetic (3070) and patient (149) OCT images were segmented for validation of our approach.
  
  
  
  The results show that the proposed 4D segmentation method is significantly more reproducible (P < 0.001) than the 3D approach and is significantly more sensitive to temporal changes (P < 0.0001) achieved by the substantial increase of measurement robustness.
  
  
  
  This is the first automated 4D method for jointly quantifying choroidal thickness in longitudinal OCT studies. Our method is robust to image noise and produces more reproducible choroidal thickness measurements than a sequence of independent 3D segmentations, without sacrificing sensitivity to temporal changes.
authors.affiliation: Department of Ophthalmology and Visual Sciences, The University of Iowa, Iowa City, Iowa, United States 2Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa, United States 3Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, United States.
authors.forename: Ipek
authors.initials: I
authors.lastname: Oguz
authors.affiliation: Department of Ophthalmology and Visual Sciences, The University of Iowa, Iowa City, Iowa, United States 2Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa, United States 4Veterans Affairs Medical Center, Iowa City, Iowa, United States.
authors.forename: Michael D
authors.initials: MD
authors.lastname: Abramoff
authors.affiliation: Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa, United States.
authors.forename: Li
authors.initials: L
authors.lastname: Zhang
authors.affiliation: Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa, United States.
authors.forename: Kyungmoo
authors.initials: K
authors.lastname: Lee
authors.affiliation: Wellman Center for Photomedicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States.
authors.forename: Ellen Ziyi
authors.initials: EZ
authors.lastname: Zhang
authors.affiliation: Department of Ophthalmology and Visual Sciences, The University of Iowa, Iowa City, Iowa, United States 2Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa, United States.
authors.forename: Milan
authors.initials: M
authors.lastname: Sonka
mesh_terms: D000368:Aged; D002829:Choroid / Q000473:pathology*; D020256:Choroidal Neovascularization / Q000175:diagnosis*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D012372:ROC Curve; D015203:Reproducibility of Results; D041623:Tomography, Optical Coherence / Q000379:methods*