Glaucoma Progression Detection Using Structural Retinal Nerve Fiber Layer Measurements and Functional Visual Field Points

@article{Yousefi2014GlaucomaPD,
  title={Glaucoma Progression Detection Using Structural Retinal Nerve Fiber Layer Measurements and Functional Visual Field Points},
  author={Siamak Yousefi and Michael H. Goldbaum and Madhusudhanan Balasubramanian and Tzyy-Ping Jung and Robert N. Weinreb and Felipe A. Medeiros and Linda M. Zangwill and Jeffrey M. Liebmann and Christopher A. Girkin and Christopher Bowd},
  journal={IEEE Transactions on Biomedical Engineering},
  year={2014},
  volume={61},
  pages={1143-1154}
}
Machine learning classifiers were employed to detect glaucomatous progression using longitudinal series of structural data extracted from retinal nerve fiber layer thickness measurements and visual functional data recorded from standard automated perimetry tests. Using the collected data, a longitudinal feature vector was created for each patient's eye by… CONTINUE READING

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