Unsupervised Gaussian Mixture-Model With Expectation Maximization for Detecting Glaucomatous Progression in Standard Automated Perimetry Visual Fields-Reference-Cited by-同舟云学术

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

Published:2016-05-03 Issue:3 Volume:5 Page:2
ISSN:2164-2591
Container-title:Translational Vision Science & Technology
language:en
Short-container-title:Trans. Vis. Sci. Tech.

Author:

Yousefi Siamak¹,Balasubramanian Madhusudhanan²,Goldbaum Michael H.¹,Medeiros Felipe A.¹,Zangwill Linda M.¹,Weinreb Robert N.¹,Liebmann Jeffrey M.³,Girkin Christopher A.⁴,Bowd Christopher¹

Affiliation:

1. Hamilton Glaucoma Center and the Department of Ophthalmology University of California San Diego, La Jolla, CA, USA

2. Department of Electrical and Computer Engineering; Department of Biomedical Engineering, University of Memphis, Memphis, TN, USA

3. Department of Ophthalmology, New York University, New York, NY, USA

4. Department of Ophthalmology, University of Alabama, Birmingham, AL, USA

Publisher

Association for Research in Vision and Ophthalmology (ARVO)

Subject

Ophthalmology,Biomedical Engineering

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