Anna Breger, Ander Biguri, Malena Sabaté Landman, Ian Selby, Nicole Amberg, Elisabeth Brunner, Janek Gröhl, Sepideh Hatamikia, Clemens Karner, Lipeng Ning, Sören Dittmer, Michael Roberts, AIX-COVNET Collaboration, Carola-Bibiane Schönlieb
A study of why we need to reassess full reference image quality assessment with medical images (submitted 2024)

Anna Breger, Clemens Karner, Ian Selby, Janek Gröhl, Sören Dittmer, Edward Lilley, Judith Babar, Jake Beckford, Timothy J Sadler, Shahab Shahipasand, Arthikkaa Thavakumar, Michael Roberts, Carola-Bibiane Schönlieb
A study on the adequacy of common IQA measures for medical images (submitted 2024)
Related code:
– speedyIQA annotation app (
– HaarPSI in PyTorch (


A. Breger
Basiswissen der mathematischen Bildbearbeitung – Zwischen Theorie und Anwendung
In print, Springer Berlin/Heidelberg, Essentials Series (2023)
DOI: 10.1007/978-3-662-68284-5

Peer-reviewed papers

  • A. Breger, C. Karner, M. Ehler
    visClust: A visual clustering algorithm based on orthogonal projections
    Pattern Recognition (Elsevier), vol 148, 2024 download
  • A. Breger, I. Selby, M. Roberts, J. Babar, J. Preller, AIX-COVNET Collaboration, J. H.F. Rudd, J. A. D. Aston, J. R. Weir-McCall, and C.-B. Schönlieb
    A pipeline to further enhance quality, integrity and reusability of the NCCID clinical data
    Scientific Data (Nature), 2023 Nature Open Access
    Online documentation:
    GitLab Code:
  • I. Selby, M. Roberts, A. Breger, J. H.F. Rudd, and J. Weir- McCall on behalf of the AIX-COVNET collaboration
    Shortcut learning: reduced but not resolved
    Radiology, 2023
  • S Dittmer, M Roberts, J Gilbey, A Biguri, I Selby, A Breger, M Thorpe, et al.
    Navigating the development challenges in creating complex data systems
    Nature Machine Intelligence, 2023  
  • I. Selby, E. G. Solares, A. Breger, M. Roberts, L. Escudero, J. H.F. Rudd, J. Babar, N. A. Walton, E. Sala, and C.-B. Schönlieb
    Automated Quality Control of Chest X-Rays
    Proceedings MIUA Cambridge, 2022
  • A.Breger, F. Goldbach, B.S. Gerendas, U. Schmidt-Erfurth, M. Ehler
    Blood vessel segmentation in en-face OCTA images: a frequency based method arXiv:2109.06116
    Proceedings of SPIE Medical Imaging, 2022
  • F. Zhang, A.Breger, K.Cho, L.Ning, C.-F. Westin, L. J. O’Donnell, and O. Pasternak
    Deep Learning Based Segmentation of Brain Tissue from Diffusion MRI ScienceDirect
    NeuroImage, vol. 223, 2021
  • A.Breger, G. Ramos Llorden, G. Vegas Sanchez – Ferrero, W. S. Hoge, M. Ehler, C.-F. Westin
    Orthogonal projections for image quality analyses applied to MRI wiley online
    Proceedings in Applied Mathematics and Mechanics, vol. 20, 2021.
  • F. Zhang, A.Breger, K.Cho, L.Ning, C.-F. Westin, L. J. O’Donnell, and O. Pasternak
    Deep Learning Based Brain Tissue Segmentation of Diffusion MRI from Novel Diffusion Kurtosis Imaging Features biorxiv
    Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), 2020
  • J.I. Orlando, B.S. Gerendas, S. Klimscha, C. Grechenig, A. Breger, M. Ehler, S.M. Waldstein, H. Bogunovic, U. Schmidt-Erfurth
    Automated Quantification of Photoreceptor alteration in macular disease using Optical Coherence Tomography and Deep Learning Nature Scientific Reports
    Scientific Reports vol. 10, 2020
  • A. Breger, J. I. Orlando, P. Harar, M. Doerfler, S. Klimscha, C. Grechenig, B. S. Gerendas, U. Schmidt-Erfurth, and M. Ehler
    On orthogonal projections for dimension reduction and applications in augmented target loss functions for learning problems Springer JMIV
    Journal of Mathematical Imaging and Vision (JMIV), vol 62, 2020
  • J. I. Orlando, A. Breger, H. Bogunović, S. Riedl, B. S. Gerendas, M. Ehler, U. Schmidt-Erfurth
    An amplified-target loss approach for photoreceptor layer segmentation in pathological OCT scans arXiv:1908.00764
    Springer Lecture Notes in Computer Science (MICCAI), 2019
  • P. Harar, R. Bammer, A. Breger, M. Doerfler, Z. Smekal
    Improving Machine Hearing on Limited Data Sets
    11th ICUMT congress (Dublin), 2019 arxiv:1903.08950
  • A. Breger, M. Ehler and M.Gräf
    Points on manifolds with asymptotically optimal covering radius arxiv:1607.06899
    Journal of Complexity, 2018
  • A. Breger, M. Ehler, H. Bogunovic, S.M. Waldstein, A. Philip, U. Schmidt-Erfurth, B.S. Gerendas
    Supervised learning and dimension reduction techniques for quantification of retinal fluid in optical coherence tomography images Epub
    Eye (Springer Nature), 2017

Book Chapters

  • A. Breger, M. Ehler, M. Gräf, T. Peter
    Cubatures on Grassmannians: moments, dimension reduction, and related topics, arXiv:1705.02978
    Compressed Sensing and its Applications: MATHEON Workshop 2015 (Applied and Numerical Harmonic Analysis), 2017
  • A. Breger, M. Ehler and M.Gräf
    Quasi Monte Carlo integration and kernel-based function approximation on Grassmannians, arXiv:1605.09165
    Frames and Other Bases in Abstract and Function Spaces, Applied and Numerical Harmonic Analysis series (ANHA, Birkhauser/Springer), 2017.


  • A.Breger, G. Ramos Llorden, G. Vegas Sanchez – Ferrero, W. S. Hoge, M. Ehler, C.-F. Westin
    On the reconstruction accuracy of multi-coil MRI with orthogonal projections, arXiv:1910.13422 (2019)


  • A. Breger
    On image segmentation and applications in clinical retinal analysis.
    Master’s thesis, University of Vienna, 2015. E-Thesis