Detecting glaucomatous change in visual fields: Analysis with an optimization framework

Eitemau Tebyg

• Learning From Data: Recognizing Glaucomatous Defect Patterns and Detecting Progression From Visual Field Measurements
  gan: Yousefi, Siamak, et al.
  Cyhoeddwyd: (2014)
• Unsupervised Gaussian Mixture-Model With Expectation Maximization for Detecting Glaucomatous Progression in Standard Automated Perimetry Visual Fields
  gan: Yousefi, Siamak, et al.
  Cyhoeddwyd: (2016)
• Patterns of Glaucomatous Visual Field Loss in Sita Fields Automatically Identified Using Independent Component Analysis
  gan: Goldbaum, Michael H., et al.
  Cyhoeddwyd: (2009)
• Deep Learning Approaches Predict Glaucomatous Visual Field Damage from Optical Coherence Tomography Optic Nerve Head Enface Images and Retinal Nerve Fiber Layer Thickness Maps
  gan: Christopher, Mark, et al.
  Cyhoeddwyd: (2019)
• Integrating Event- and Trend-based Analyses to Improve Detection of Glaucomatous Visual Field Progression
  gan: Medeiros, Felipe A., et al.
  Cyhoeddwyd: (2012)