Jeffrey M. Liebmann

发表

Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs

Christopher Bowd, Linda M. Zangwill, Robert N. Weinreb, 2018, Scientific Reports.

A Test of a Schematic Model of Glaucomatous Damage of the Macula

Donald C. Hood, Jeffrey M. Liebmann, Ali S. Raza, 2013 .

Early detection of visual field conversion using an unsupervised machine-learning analysis of retinal nerve fiber layer thickness measurements

Christopher Bowd, Linda M. Zangwill, Felipe A. Medeiros, 2016 .

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

Christopher Bowd, Linda M. Zangwill, Felipe A. Medeiros, 2015, J. Biomed. Informatics.

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

Tzyy-Ping Jung, Christopher Bowd, Linda M. Zangwill, 2014, IEEE Transactions on Biomedical Engineering.

Combining Visual Field and Frequency Domain OCT Data Improves Detection of Glaucoma

Donald C. Hood, Jeffrey M. Liebmann, Xian Zhang, 2012 .

Deep Learning Models Predict Visual Function from Macula Thickness Map

Christopher Bowd, Linda M. Zangwill, Robert N. Weinreb, 2019 .

Learning From Data: Recognizing Glaucomatous Defect Patterns and Detecting Progression From Visual Field Measurements

Christopher Bowd, Linda M. Zangwill, Felipe A. Medeiros, 2014, IEEE Transactions on Biomedical Engineering.

Recognizing glaucomatous defect patterns and detecting progression from visual field measurements using Gaussian mixture model and expectation maximization

Christopher Bowd, Linda M. Zangwill, Felipe A. Medeiros, 2014 .

Combining Structural (Visual Field) and Functional (OCT) Information to Confirm Early Glaucoma: A Topographical Method is Better Than Metrics.

Donald C. Hood, Jeffrey M. Liebmann, C Gustavo De Moraes, 2018 .

The 24-2 visual field is not a substitute for the 10-2 for detecting early central damage.

Emmanouil Tsamis, Donald C. Hood, Jeffrey M. Liebmann, 2020 .

Systems for staging glaucoma based upon 24-2 visual fields have a fundamental flaw.

Donald C. Hood, Jeffrey M. Liebmann, C Gustavo De Moraes, 2017 .

Predicting Glaucomatous Progression from Baseline HRT and SAP Measurements Using Relevance Vector Machine (RVM) Classifiers

Christopher Bowd, Linda M. Zangwill, Felipe A. Medeiros, 2011 .

Unsupervised Machine Learning With Independent Component Analysis Identifies Patterns of Glaucomatous Visual Field Loss in SITA Fields

Christopher Bowd, Jiucang Hao, Linda M. Zangwill, 2009 .

Short-duration transient visual evoked potential for objective measurement of refractive errors

Jeffrey M. Liebmann, Robert Ritch, Aashish Anand, 2011, Documenta Ophthalmologica.

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

Christopher Bowd, Linda M. Zangwill, Felipe A. Medeiros, 2016, Translational vision science & technology.

Does Changing Eye Test Order With 24–2 SITA Standard Result in a Meaningful Change in Test Results?

Jeffrey M. Liebmann, Ricardo Mora, Yaniv Barkana, 2005 .

Unsupervised machine learning to recognize glaucoma defect patterns and detect progression in RNFL thickness measurements

Christopher Bowd, Linda M. Zangwill, Felipe A. Medeiros, 2015 .

Glaucomatous patterns of binocular visual field loss identified by unsupervised machine learning

Christopher Bowd, Linda M. Zangwill, Felipe A. Medeiros, 2014 .

Possible indices for minimizing false positives on the multifocal VEP test.

Donald C. Hood, Jeffrey M. Liebmann, Nitin Ohri, 2004 .

A Comparison of Visual Field Abnormalities Detected by Multifocal VEPs and Static Achromatic Automated Perimetry

Donald C. Hood, Xian Zhang, Jeffrey M. Liebmann, 2003 .

A Continuous Classification System for Glaucomatous Visual Field

Donald C. Hood, Jeffrey M. Liebmann, Xian Zhang, 2012 .

Individualized deep learning auto-encoder (DL-AE)-based OCT deviation maps for improved glaucoma progression detection

Christopher Bowd, Linda M. Zangwill, Robert N. Weinreb, 2020 .

A Comparison of Short-Wavelength Automated Perimetry Using the Swedish Interactive Threshold Algorithm (SWAP-SITA) to the Full-Threshold method (SWAP-FT) and Standard Automated Perimetry (SAP-SITA)

Linda M. Zangwill, Pamela A. Sample, Robert N. Weinreb, 2008 .

Detection of Glaucoma Using Operator–Dependent Versus Operator–Independant Classification in the HRT–III

Jeffrey M. Liebmann, Celso Tello, R. Ritch, 2006 .

a ten year review

Jeffrey M. Liebmann, Robert Ritch, David C. Ritterband, 1998 .

Detection and measurement of clinically meaningful visual field progression in clinical trials for glaucoma

Jeffrey M. Liebmann, Leonard A. Levin, L. Levin, 2017, Progress in Retinal and Eye Research.

Repeatability of short-duration transient visual evoked potentials in normal subjects

Jeffrey M. Liebmann, Robert Ritch, Celso Tello, 2010, Documenta Ophthalmologica.

Glaucomatous Damage of the Macula as Revealed by Averaging Optical Coherence Tomography Data

Donald C. Hood, Jeffrey M. Liebmann, Ali S. Raza, 2012 .

Effects of Study Population, Labeling and Training on Glaucoma Detection Using Deep Learning Algorithms

Christopher Bowd, Linda M. Zangwill, Robert N. Weinreb, 2020, Translational vision science & technology.

Estimated retinal ganglion cell counts in glaucomatous eyes with localized retinal nerve fiber layer defects.

Linda M. Zangwill, Felipe A. Medeiros, Robert N. Weinreb, 2013, American journal of ophthalmology.

Detection of Glaucoma Progression in Individuals of African Descent Compared With Those of European Descent

Linda M. Zangwill, Felipe A. Medeiros, Robert N. Weinreb, 2018, JAMA ophthalmology.

Progression pattern of initial parafoveal scotomas in glaucoma.

Jeffrey M. Liebmann, Robert Ritch, R. Ritch, 2013, Ophthalmology.

Detecting the inner and outer borders of the retinal nerve fiber layer using optical coherence tomography

Hiroshi Ishikawa, Jeffrey M. Liebmann, Robert Ritch, 2002, Graefe's Archive for Clinical and Experimental Ophthalmology.

Glaucomatous Patterns in Frequency Doubling Technology (FDT) Perimetry Data Identified by Unsupervised Machine Learning Classifiers

Christopher Bowd, Linda M. Zangwill, Felipe A. Medeiros, 2014, PloS one.

Comparison of Visual Field Severity Classification Systems for Glaucoma

Linda M. Zangwill, Pamela A. Sample, Robert N. Weinreb, 2012, Journal of glaucoma.

A Comparison of Retinal Nerve Fiber (RNFL) Thickness Obtained With Frequency and Time Domain Standard Optical Coherence Tomography (OCT)

Donald C. Hood, Jeffrey M. Liebmann, Ali S. Raza, 2008 .

Imaging of the optic disc and retinal nerve fiber layer in acute optic neuritis

Jeffrey M. Liebmann, Robert Ritch, Mauricio E Pons, 2006, Journal of the Neurological Sciences.

Glaucomatous damage of the macula

Donald C. Hood, Jeffrey M. Liebmann, Ali S. Raza, 2013, Progress in Retinal and Eye Research.

Macular and Retinal Nerve Fiber Layer Thickness Measurement Reproducibility Using Optical Coherence Tomography (OCT-3)

Jeffrey M. Liebmann, Robert Ritch, Christopher Teng, 2003, Journal of glaucoma.

Microarchitecture of Schlemm Canal Before and After Selective Laser Trabeculoplasty in Enhanced Depth Imaging Optical Coherence Tomography

Alon Skaat, Jeffrey M. Liebmann, Robert Ritch, 2017, Journal of glaucoma.