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Stefan Ploner, M. Sc.

Researcher

Department of Computer Science
Chair of Computer Science 5 (Pattern Recognition)

Room: Room 09.130
Martensstr. 3
91058 Erlangen

Office hours

VISTA showing neovascularization having slow flow in PDR case

VISTA revealing slower blood flow in neovascularization (top-left of FAZ) in an OCTA scan of a 30 y/o PDR patient.

Since its recent transfer from research to the clinic, OCT Angiography (OCTA) is revolutionizing the field of ophthalmic Optical Coherence Tomography (OCT). Whereas OCTA provides detailed information on vasculature today, to take full advantage, novel image processing algorithms are still to be developed. For example, algorithms like Variable Interscan Time Analysis (VISTA) could add the whole new dimension of blood flow speed to OCT data, and more advanced removal of decorrelation tail artifacts could improve the analysis of the deep vascular layer. An ongoing research topic of our group is the correction of motion artifacts, which have an especially high impact on OCTA data. Robust and accurate motion correction is thus essential for the reconstruction of high quality OCTA signals, however, current algorithms do not yet model the newer OCTA scanning protocols precisely.

The goal of my PhD is to fill these gaps and to bring these promising advancements to the clinic. To make this possible, I’m in close collaboration with the Biomedical Optical Imaging and Biophotonics Group at the Massachusetts Institute of Technology, Cambridge, USA, the group who built the first and still develops most advanced ophthalmic OCT systems to date, and the New England Eye Center, Boston, USA, the first clinic that used OCT technology in patient care.

Since 07/2017: PhD Student, Pattern Recognition Lab, Friedrich-Alexander University Erlangen-Nürnberg

  • Research focus on motion correction and enhanced signal reconstruction in the field
    of Optical Coherence Tomography (OCT) and OCT angiography (OCTA)
  • In collaboration with the Biomedical Optical Imaging and Biophotonics Group,
    Massachusetts Institute of Technology, Cambridge, USA
  • Article on motion correction in OCTA among the ~5% highlighted as Editor’s pick in Biomedical Optics Express
  • Journal reviewer for BOEx, IOVS (“exceptional reviewer”), JBio, JBO, TVST, and others.

10/2014 – 05/2017: Master of Science with distinction in Computer Science, Friedrich-Alexander University Erlangen-Nürnberg

  • Focus on medical image processing, pattern recognition and high-performance computing
  • Master thesis: Improving 3D OCT motion correction

10/2015 – 05/2016: Visiting student, Massachusetts Institute of Technology, Cambridge, USA

04/2011 – 03/2015: Bachelor of Science in Computer Science, Friedrich-Alexander University Erlangen-Nürnberg

  • Focus on pattern recognition, computer architecture, discrete optimization and computer graphics
  • Student research assistant at the Pattern Recognition Lab, research on false
    color visualization in the multispectral imaging software framework Gerbil

09/2001 – 06/2010: University entrance diploma (Abitur), Emil-von-Behring-Gymnasium, Spardorf

Teaching Experience

  • 10/2014 – 01/2015: Student teaching assistant, Friedrich-Alexander University Erlangen-Nürnberg
    • Exercises in Theory of Computation and Formal Languages
  • 10/2011 – 09/2012: Student teaching assistant, Friedrich-Alexander University Erlangen-Nürnberg
    • Exercises in Algorithms and Data Structures

2017

  • Joint Iterative Reconstruction and Motion Compensation for Optical Coherence Tomography
    Angiography

    (Third Party Funds Single)

    Term: since July 24, 2017
    Funding source: DFG-Einzelförderung / Sachbeihilfe (EIN-SBH)

    Optical coherence tomography (OCT) is a non-invasive 3-D optical imagingmodality that is a standard of care in ophthalmology [1,2]. Since the introduction of Fourier-domain OCT [3], dramatic increases in imaging speedbecame possible, enabling 3-D volumetric data to be acquired. Typically, aregion of the retina is scanned line by line, where each scanned lineacquires a cross-sectional image or a B-scan. Since B-scans are acquiredin milliseconds, slices extracted along a scan line, or the fast scanaxis, are barely affected by motion. In contrast, slices extractedorthogonally to scan lines, i. e. in slow scan direction, areaffected by various types of eye motion occurring throughout the full,multi-second volume acquisition time. The most relevant types of eyemovements during acquisition are (micro-)saccades, which can introducediscontinuities or gaps between B-scans, and slow drifts, which causesmall, slowly changing distortion [4]. Additional eye motion is caused by pulsatile blood flow,respiration and head motion. Despite ongoing advances in instrumentscanning speed [5,6] typical volume acquisition times havenot decreased. Instead, the additional scanning speed is used for densevolumetric scanning or wider fields of view [7]. OCT angiography (OCTA) [811] multiplies therequired number of scans by at least two, and even more scans are neededto accommodate recent developments in blood flow speed estimation whichare based on multiple interscan times [12,13]. As a consequence,there is an ongoing need for improvement in motion compensation especiallyin pathology [1416].

    We develop novel methods for retrospective motion correction of OCT volume scans of the anterior and posterior eye, and widefield imaging. Our algorithms are clinically usable due to their suitability for patients with limited fixation capabilities and increased amount of motion, due to their fast processing speed, and their high accuracy, both in terms of alignment and motion correction. By merging multiple accurately aligned scans, image quality can be increased substantially, enabling the inspection of novel features.

2021

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2020

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2019

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2018

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Book Contributions

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2017

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2016

Journal Articles

Conference Contributions