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Detail

Wolf-Dieter Vogl
Dipl.-Ing. Wolf-Dieter Vogl, PhD

Department of Ophthalmology and Optometry
Position: Research Associate (Postdoc)

ORCID: 0000-0003-2197-5838
T +43 1 40400 67600
wolf-dieter.vogl@meduniwien.ac.at

Further Information

Keywords

Artificial Intelligence; Diabetic Retinopathy; Diagnosis, Computer-Assisted; Diagnostic Imaging; Macular Degeneration; Magnetic Resonance Imaging; Retinal Vein Occlusion; Tomography, Optical Coherence

Research group(s)

Research interests

  • Spatio-temporal model building and analysis
  • Longitudinal medical image analysis
  • Sparse and Non-linear Regression
  • Image Registration
  • Multi-Modality Image Analysis
  • Computer Aided Diagnosis Systems

Techniques, methods & infrastructure

  • Machine learning (Random Forests, Deep learning)
  • Statistical machine learning (Sparse models, Elastic Net)
  • Longitudinal mixed effects models, Joint models
  • Large-scale medical image processing
  • Population modelling of ophthalmic imaging data
  • High-performance computing (HPC)

Selected publications

  1. Vogl, W.-D. et al., 2017. Predicting Macular Edema Recurrence from Spatio-Temporal Signatures in Optical Coherence Tomography Images. IEEE Transactions on Medical Imaging, pp.1-1. Available at: http://dx.doi.org/10.1109/TMI.2017.2700213.
  2. Vogl, W.-D. et al., 2015. Spatio-Temporal Signatures to Predict Retinal Disease Recurrence. Information Processing in Medical Imaging, pp.152-163. Available at: http://dx.doi.org/10.1007/978-3-319-19992-4_12.
  3. Vogl, W.-D. et al., 2014. Longitudinal Alignment of Disease Progression in Fibrosing Interstitial Lung Disease. Lecture Notes in Computer Science, pp.97-104. Available at: http://dx.doi.org/10.1007/978-3-319-10470-6_13.
  4. Vogl, W.-D. et al., 2017. Analyzing and Predicting Visual Acuity Outcomes of Anti-VEGF Therapy by a Longitudinal Mixed Effects Model of Imaging and Clinical Data. Investigative Opthalmology & Visual Science, 58(10), p.4173. Available at: http://dx.doi.org/10.1167/iovs.17-21878.