Patterns of Glaucomatous Visual Field Loss in Sita Fields Automatically Identified Using Independent Component Analysis

Lignende værker

• Using Unsupervised Learning with Independent Component Analysis to Identify Patterns of Glaucomatous Visual Field Defects
  af: Goldbaum, Michael H., et al.
  Udgivet: (2005)
• Detecting glaucomatous change in visual fields: Analysis with an optimization framework
  af: Yousefi, Siamak, et al.
  Udgivet: (2015)
• Unsupervised Machine Learning with Independent Component Analysis to Identify Areas of Progression in Glaucomatous Visual Fields
  af: Sample, Pamela A., et al.
  Udgivet: (2005)
• Learning From Data: Recognizing Glaucomatous Defect Patterns and Detecting Progression From Visual Field Measurements
  af: Yousefi, Siamak, et al.
  Udgivet: (2014)
• Unsupervised Gaussian Mixture-Model With Expectation Maximization for Detecting Glaucomatous Progression in Standard Automated Perimetry Visual Fields
  af: Yousefi, Siamak, et al.
  Udgivet: (2016)