Unsupervised Gaussian Mixture-Model With Expectation Maximization for Detecting Glaucomatous Progression in Standard Automated Perimetry Visual Fields

PURPOSE: To validate Gaussian mixture-model with expectation maximization (GEM) and variational Bayesian independent component analysis mixture-models (VIM) for detecting glaucomatous progression along visual field (VF) defect patterns (GEM–progression of patterns (POP) and VIM-POP). To compare GEM-...

Popoln opis

Shranjeno v:
Bibliografske podrobnosti
izdano v:Transl Vis Sci Technol
Main Authors: Yousefi, Siamak, Balasubramanian, Madhusudhanan, Goldbaum, Michael H., Medeiros, Felipe A., Zangwill, Linda M., Weinreb, Robert N., Liebmann, Jeffrey M., Girkin, Christopher A., Bowd, Christopher
Format: Artigo
Jezik:Inglês
Izdano: The Association for Research in Vision and Ophthalmology 2016
Teme:
Articles
Online dostop:https://ncbi.nlm.nih.gov/pmc/articles/PMC4855479/
https://ncbi.nlm.nih.gov/pubmed/27152250
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1167/tvst.5.3.2
Oznake: Označite
Brez oznak, prvi označite!

Podobne knjige/članki