title: Automated anterior segment OCT image analysis for Angle Closure Glaucoma mechanisms classification.
abstract: OBJECTIVE
  Angle closure glaucoma (ACG) is an eye disease prevalent throughout the world. ACG is caused by four major mechanisms: exaggerated lens vault, pupil block, thick peripheral iris roll, and plateau iris. Identifying the specific mechanism in a given patient is important because each mechanism requires a specific medication and treatment regimen. Traditional methods of classifying these four mechanisms are based on clinically important parameters measured from anterior segment optical coherence tomography (AS-OCT) images, which rely on accurate segmentation of the AS-OCT image and identification of the scleral spur in the segmented AS-OCT images by clinicians.
  
  
  METHODS
  In this work, a fully automated method of classifying different ACG mechanisms based on AS-OCT images is proposed. Since the manual diagnosis mainly based on the morphology of each mechanism, in this study, a complete set of morphological features is extracted directly from raw AS-OCT images using compound image transforms, from which a small set of informative features with minimum redundancy are selected and fed into a Naïve Bayes Classifier (NBC).
  
  
  RESULTS
  We achieved an overall accuracy of 89.2% and 85.12% with a leave-one-out cross-validation and 10-fold cross-validation method, respectively. This study proposes a fully automated way for the classification of different ACG mechanisms, which is without intervention of doctors and less subjective when compared to the existing methods.
  
  
  CONCLUSIONS
  We directly extracted the compound image transformed features from the raw AS-OCT images without any segmentation and parameter measurement. Our method provides a completely automated and efficient way for the classification of different ACG mechanisms.
authors.affiliation: School of Computer Engineering, Nanyang Technological University (NTU), 639798 Singapore, Singapore. Electronic address: issacniwas@ntu.edu.sg.
authors.forename: Swamidoss Issac
authors.initials: SI
authors.lastname: Niwas
authors.affiliation: School of Computer Engineering, Nanyang Technological University (NTU), 639798 Singapore, Singapore. Electronic address: wslin@ntu.edu.sg.
authors.forename: Weisi
authors.initials: W
authors.lastname: Lin
authors.affiliation: The State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou 310027, People's Republic of China; School of Electrical and Electronics Engineering, Nanyang Technological University (NTU), 639798 Singapore, Singapore. Electronic address: mebaixl@gmail.com.
authors.forename: Xiaolong
authors.initials: X
authors.lastname: Bai
authors.affiliation: School of Computer Engineering, Nanyang Technological University (NTU), 639798 Singapore, Singapore. Electronic address: asckkwoh@ntu.edu.sg.
authors.forename: Chee Keong
authors.initials: CK
authors.lastname: Kwoh
authors.affiliation: Ming Hsieh Department of Electrical Engineering, Signal and Image Processing Institute, University of Southern California, Los Angeles, CA 90089, USA. Electronic address: cckuo@sipi.usc.edu.
authors.forename: C-C
authors.initials: CC
authors.lastname: Jay Kuo
authors.affiliation: Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore (NUS), 119228 Singapore, Singapore. Electronic address: chelvin@gmail.com.
authors.forename: Chelvin C
authors.initials: CC
authors.lastname: Sng
authors.affiliation: Eye Surgery Centre, National University Health System (NUHS), 119228 Singapore, Singapore. Electronic address: mcdaquino@gmail.com.
authors.forename: Maria Cecilia
authors.initials: MC
authors.lastname: Aquino
authors.affiliation: Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore (NUS), 119228 Singapore, Singapore. Electronic address: ophchewp@nus.edu.sg.
authors.forename: Paul T K
authors.initials: PT
authors.lastname: Chew
mesh_terms: D000869:Anterior Eye Segment / Q000473:pathology*; D015812:Glaucoma, Angle-Closure / Q000473:pathology*; D006801:Humans; D041623:Tomography, Optical Coherence
keywords: Angle closure glaucoma; Compound image transforms; Feature selection; Machine learning classifier; Segmentation-free method