Recurrent neural network based retinal nerve fiber layer defect detection in early glaucoma

@article{Panda2017RecurrentNN,
  title={Recurrent neural network based retinal nerve fiber layer defect detection in early glaucoma},
  author={Rashmi Panda and Niladri B. Puhan and Aparna Rao and Debananda Padhy and Ganapati Panda},
  journal={2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)},
  year={2017},
  pages={692-695}
}
Retinal nerve fiber layer defect (RNFLD) is the earliest objective evidence of glaucoma in fundus images. Glaucoma is an optic neuropathy which causes irreversible vision impairment. Early glaucoma detection and its prevention are the only way to prevent further damage to human vision. In this paper, we propose a new automated method for RNFLD detection in fundus images through patch features driven recurrent neural network (RNN). A new dataset of fundus images is created for evaluation purpose… CONTINUE READING
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