Classification of healthy and diseased retina using SD-OCT imaging and Random Forest algorithm
Md Akter Hussain, Alauddin Bhuiyan, Chi D Luu, R Theodore Smith, Robyn H Guymer, Hiroshi Ishikawa, Joel S Schuman, Kotagiri Ramamohanarao
PLOS ONE | PUBLIC LIBRARY SCIENCE | Published : 2018
In this paper, we propose a novel classification model for automatically identifying individuals with age-related macular degeneration (AMD) or Diabetic Macular Edema (DME) using retinal features from Spectral Domain Optical Coherence Tomography (SD-OCT) images. Our classification method uses retinal features such as the thickness of the retina and the thickness of the individual retinal layers, and the volume of the pathologies such as drusen and hyper-reflective intra-retinal spots. We extract automatically, ten clinically important retinal features by segmenting individual SD-OCT images for classification purposes. The effectiveness of the extracted features is evaluated using several cla..View full abstract
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Awarded by Principal Research Fellowship
Awarded by Australian Research Council (ARC)
This research is funded by three funds. M.A. Hussain is supported by the University of Melbourne International PhD Research Scholarship. R.H. Guymer is supported by Principal Research Fellowship (1103013). K. Ramamohanarao is supported by Australian Research Council (ARC DP110102621).