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Dive into the research topics where Ana-Maria Glodan is active.

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Featured researches published by Ana-Maria Glodan.


information processing in medical imaging | 2015

Spatio-Temporal Signatures to Predict Retinal Disease Recurrence

Wolf-Dieter Vogl; Sebastian M. Waldstein; Bianca S. Gerendas; Christian Simader; Ana-Maria Glodan; Dominika Podkowinski; Ursula Schmidt-Erfurth; Georg Langs

We propose a method to predict treatment response patterns based on spatio-temporal disease signatures extracted from longitudinal spectral domain optical coherence tomography (SD-OCT) images. We extract spatio-temporal disease signatures describing the underlying retinal structure and pathology by transforming total retinal thickness maps into a joint reference coordinate system. We formulate the prediction as a multi-variate sparse generalized linear model regression based on the aligned signatures. The algorithm predicts if and when recurrence of the disease will occur in the future. Experiments demonstrate that the model identifies predictive and interpretable features in the spatio-temporal signature. In initial experiments recurrence vs. non-recurrence is predicted with a ROC AuC of 0.99. Based on observed longitudinal morphology changes and a time-to-event based Cox regression model we predict the time to recurrence with a mean absolute error (MAE) of 1.25 months comparing favorably to elastic net regression (1.34 months), demonstrating the benefit of a spatio-temporal survival model.


Eye | 2015

Comparison of penetration depth in choroidal imaging using swept source vs spectral domain optical coherence tomography

Sebastian M. Waldstein; Henrik Faatz; Szimacsek M; Ana-Maria Glodan; Dominika Podkowinski; Alessio Montuoro; Christian Simader; Bianca S. Gerendas; Ursula Schmidt-Erfurth

PurposeTo compare signal penetration depth and deep structure-visualization of swept source (SS) and spectral domain (SD)-optical coherence tomography (OCT) with and without enhanced depth imaging (EDI) and B-scan averaging modes.MethodsVolume scans were obtained from 20 eyes of healthy volunteers by DRI OCT-1, Spectralis using EDI and B-scan averaging, and Cirrus HD-OCT. The signal penetration depth was measured as the distance between the retinal pigment epithelium and the deepest visible anatomical structure at the foveal center. Visibility and contrast of the choroidoscleral junction and of vascular details within the choroid were assessed across the entire volume using an ordinal scoring scale. Outcome measures were compared using paired t-test and rank-sum test.ResultsThe mean signal penetration depth was 498±114 μm for Spectralis, 491±85 μm for DRI OCT-1, and 123±65 μm for Cirrus; P=0.9708 Spectralis vs DRI OCT-1, P<0.0001 Spectralis vs Cirrus, and P<0.0001 DRI OCT-1 vs Cirrus. Mean ranks for visibility and contrast of the choroidoscleral junction were 3.83 for Spectralis, 3.98 for DRI OCT-1, and 2.00 for Cirrus; and 3.45 for Spectralis, 2.93 for DRI OCT-1, and 1.58 for Cirrus. Mean ranks for visibility and contrast of vascular details were 3.73 (Spectralis), 3.70 (DRI OCT-1), and 2.23 (Cirrus); and 3.53 (Spectralis), 2.05 (DRI OCT-1), and 1.98 (Cirrus).ConclusionSignal penetration depths are similar for SS-OCT and SD-OCT using EDI and frame averaging, and statistically significantly lower without EDI/averaging. Both SD-OCT using EDI/frame averaging and SS-OCT offer excellent visualization capabilities for volumetric imaging of the choroidoscleral interface.


Investigative Ophthalmology & Visual Science | 2015

Automatic segmentation and classification of intraretinal cystoid fluid and subretinal fluid in 3D-OCT using convolutional neural networks

Thomas Schlegl; Ana-Maria Glodan; Dominika Podkowinski; Sebastian M Waldstein; Bianca S. Gerendas; Ursula Schmidt-Erfurth; Georg Langs


Investigative Ophthalmology & Visual Science | 2015

Automatic segmentation of the posterior vitreous boundary in retinal optical coherence tomography

Alessio Montuoro; Sebastian M Waldstein; Ana-Maria Glodan; Dominika Podkowinski; Bianca S. Gerendas; Georg Langs; Christian Simader; Ursula Schmidt-Erfurth


Investigative Ophthalmology & Visual Science | 2015

Three-dimensional analysis of intra- and subretinal fluid provides precise prediction of visual acuity in neovascular AMD

Sebastian M. Waldstein; Ana-Maria Glodan; Roland Leitner; Christian Simader; Georg Langs; Bianca S. Gerendas; Ursula Schmidt-Erfurth


Investigative Ophthalmology & Visual Science | 2015

The foveal shape is not predictive of visual acuity and treatment response in macular edema due to retinal vein occlusion

Dominika Podkowinski; Jing Wu; Ana-Maria Glodan; Bianca S. Gerendas; Alessio Montuoro; Roland Leitner; Christian Simader; Sebastian M Waldstein; Ursula Schmidt-Erfurth


Investigative Ophthalmology & Visual Science | 2015

A Multi-vendor Dataset and Standardized Evaluation Framework for Retinal Cyst Segmentation

Christian Simader; Jing Wu; Ana-Maria Glodan; Sebastian M Waldstein; Bianca S. Gerendas; Georg Langs; Ursula Schmidt-Erfurth


Investigative Ophthalmology & Visual Science | 2015

Disease-modeling-based prediction of recurrence patterns in anti-VEGF therapy from OCT analyses

Ursula Schmidt-Erfurth; Wolf-Dieter Vogl; Dominika Podkowinski; Ana-Maria Glodan; Bianca S. Gerendas; Alessio Montuoro; Jing Wu; Christian Simader; Georg Langs; Sebastian M. Waldstein


Investigative Ophthalmology & Visual Science | 2015

Predictive value of individual and regional retinal layer thickness on visual acuity and functional outcomes in the therapy of retinal vein occlusion

Ana-Maria Glodan; Sebastian M Waldstein; Dominika Podkowinski; Alessio Montuoro; Wolf-Dieter Vogl; Roland Leitner; Christian Simader; Bianca S. Gerendas; Ursula Schmidt-Erfurth


Investigative Ophthalmology & Visual Science | 2014

Reproducibility of automated choroidal thickness measurements: swept-source OCT and spectral-domain OCT using enhanced depth imaging

Li Zhang; Michael D. Abràmoff; Sebastian M. Waldstein; Bianca S. Gerendas; Ana-Maria Glodan; Christian Simader; Ursula Schmidt-Erfurth; Milan Sonka

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Bianca S. Gerendas

Medical University of Vienna

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Christian Simader

Medical University of Vienna

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Dominika Podkowinski

Medical University of Vienna

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Georg Langs

Medical University of Vienna

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Alessio Montuoro

Medical University of Vienna

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Jing Wu

Medical University of Vienna

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Roland Leitner

Medical University of Vienna

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