Automatic Feature Learning to Grade Nuclear Cataracts Based on Deep Learning

@article{Gao2015AutomaticFL,
  title={Automatic Feature Learning to Grade Nuclear Cataracts Based on Deep Learning},
  author={X. Gao and Stephen Lin and T. Wong},
  journal={IEEE Transactions on Biomedical Engineering},
  year={2015},
  volume={62},
  pages={2693-2701}
}
  • X. Gao, Stephen Lin, T. Wong
  • Published 2015
  • Computer Science, Medicine
  • IEEE Transactions on Biomedical Engineering
  • Goal: Cataracts are a clouding of the lens and the leading cause of blindness worldwide. [...] Key Method Local filters are first acquired through clustering of image patches from lenses within the same grading class. The learned filters are fed into a convolutional neural network, followed by a set of recursive neural networks, to further extract higher order features. With these features, support vector regression is applied to determine the cataract grade. Results: The proposed system is validated on a large…Expand Abstract
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