Submitted

 

  • Discretization of learned NETT regularization for solving inverse problems
    S. Antholzer and M. Haltmeier
    Submitted, 2020 [arxiv.org]

  • Regularization of Inverse Problems by Filtered Diagonal Frame Decomposition
    A. Ebner, J. Frikel, D. Lorenz, J. Schwab, M. Haltmeier
    Submitted, 2020  [arxiv.org]

  • Sparse  ℓ^q-regularization of inverse problems with deep learning
    M. Haltmeier, L. Nguyen, D. Obmann, J. Schwab
    Submitted, 2019 [arxiv.org]

  • Regularization of inverse problems by neural networks
    M. Haltmeier, L.V. Nguyen
    Submitted, 2020 [pdf pdf button][arxiv.org]

  • The conical Radon transform with vertices on triple lines
    M. Haltmeier, S. Moon
    Submitted, 2020 [pdf pdf button][arxiv.org]

  • Unsupervised adaptive neural network regularization for accelerated radial cine MRI
    A. Kofler, M. Dewey, T. Schaeffter, C. Kolbitsch, M. Haltmeier
    Submitted, 2020 [pdf pdf button][arxiv.org]

  • Data-consistent neural networks for solving nonlinear inverse problems
    Y. E. Boink, M. Haltmeier, S. Holman, J. Schwab
    Submitted, 2020 [pdf pdf button][arxiv.org]

 

Published 2021

     
  • Published 2020

    • A joint deep learning approach for automated liver and tumor segmentation
      N. Gruber, S. Antholzer, W. Jaschke, C. Kremser, M. Haltmeier
      IEEE SampTA (9030909), pp.1-5, 2020
    • Breaking the resolution limit in photoacoustic imaging using positivity and sparsity
      P. Burgholzer, J. Bauer-Marschallinger, M. Hettich, M. Haltmeier
      Proc. SPIE, Vol. 11240, pp.232-238, 2020
    • Photoacoustic reconstruction from photothermal measurements including prior information
      G. Thummerer, G. Mayr, M. Haltmeier, P. Burgholzer
      Photoacoustics 19, 2020
    • Phospholipid acyl chain diversity controls the tissue-specific assembly of mitochondrial cardiolipins
      G. Oemer, J. Koch, Y. Wohlfarter, M.T. Alam, K. Lackner, S. Sailer, L. Neumann, H.H. Lindner, K. Watschinger, M. Haltmeier, E.R. Werner, J. Zschocke, M.A. Keller
      Cell Rep 30(12), pp.4281-4291, 2020
    • A machine learning framework for customer purchase prediction in the non-contractual setting
      A. Martínez, C. Schmuck, S. Pereverzyev Jr., C. Pirker, M. Haltmeier
      Eur J Oper Res 281(3), pp.588-596, 2020 [pdf pdf button]
    • NETT: solving inverse problems with deep neural networks
      H. Li, J. Schwab, S. Antholzer, M. Haltmeier
      Invers Probl, 2020 [pdf pdf button] [arxiv.org]

     

    Published 2019

    • Full field inversion in photoacoustic tomography with variable sound speed
      G. Zangerl. M. Haltmeier, L.V. Nguyen,R.Nuster
      Appl Sci 9(8):1563, 2019 [arxiv.org]
    • Photoacoustic image reconstruction from full field data in heterogeneous media
      M. Haltmeier, G. Zangerl, L.V. Nguyen, R. Nuster
      Proc. SPIE, Vol. 10878, 2019
    • Deep Learning of truncated singular values for limited view photoacoustic tomography
      J. Schwab, S. Antholzer, R. Nuster, G. Paltauf, M. Haltmeier
      Porc. SPIE, Vol. 10878, 2019
    • Learned backprojection for sparse and limited view photoacoustic tomography
      J. Schwab, S. Antholzer, M. Haltmeier
      Proc. SPIE, Vol. 10878, 2019
    • NETT regularization for compressed sensing photoacoustic tomography
      A. Antholzer, J. Schwab, J. Bauer-Marschallinger, P. Burgholzer, M. Haltmeier
      Proc. SPIE, Vol. 10878, 2019
    • Compressive time-of-flight 3D imaging using block-structured sensing matrices
      S. Antholzer, C. Wolf, M. Sandbichler, M. Dielacher and M. Haltmeier
      Inverse Probl 35(04), pp.18, 2019 [pdf pdf button] [arxiv.org]

     

    Published 2018

    • Pipe failure modelling for water distribution networks using boosted decision trees
      D. Winkler, M. Haltmeier, M. Kleindorfer, W. Rauch, F. Tscheikner-Gratl
      Struct Infrastruct E 14(10), pp.1402-1411, 2018
    • A new sparsification and reconstruction strategy for compressed sensing photoacoustic tomography
      M. Haltmeier, M. Sandbichler, T. Berer, J. Bauer-Marschallinger, P. Burgholzer, L. Nguyen
      J. Acoust Soc Am 143(6), 3838, 2018 [pdf pdf button] [arxiv.org]
    • Photoacoustic image reconstruction via deep learning
      S. Antholzer, M. Haltmeier, R. Nuster, J. Schwab
      Proc. SPIE 10494:104944U, 2018 [pdf pdf button]
    • Stochastic proximal gradient algorithms for multi-source quantitative photoacoustic tomography
      S. Rabanser, L. Neumann, M. Haltmeier
      Entropy, 20(2):121, 2018 [pdf pdf button] [arxiv.org]
    • Galaxy and mass assembly: automatic morphological classification of galaxies using statistical learning
      S. Sreejith, S. Pereverzyev Jr., L.S. Kelvin, F. Marleau, M. Haltmeier, J. Ebner, et al.
      Mon. Notices Royal Astron Soc 474(4), pp.5232-5258, 2018

     

    Published 2017

    • Low-rank approximation for FMCW automotive radar
      J. Sappl, P. Meissner, M. Haltmeier
      Proc. SampTA (IEEE), 2017
    • Compressive time-of-flight imaging
      S. Antholzer, C. Wolf, M. Sandbichler, M. Dielacher, M. Haltmeier
      Proc. SampTA (IEEE), 2017
    • Super-resolution photoacoustic microscopy using joint sparsity
      P. Burgholzer, M. Haltmeier, T. Berer, E. Leiss-Holzinger, T. W. Murray
      Proc. SPIE. 10415:1041506, 2017
    • Nyström type subsampling analyzed as a regularized projection
      G. Kriukova, S. Pereverzyev Jr., P. Tkachenko
      Inverse Probl 33(7):074001, 2017 [pdf pdf button]
    • Compressed sensing in photoacoustic imaging and application for planar detection geometries
      T. Berer, P. Burgholzer, M. Haltmeier
      Proc. SPIE 10064:100642, 2017
    • Super-resolution photoacoustic microscopy using blind structured illumination
      T. W. Murray, M. Haltmeier, T. Berer, E. Leiss-Holzinger and P. Burgholzer
      Optica 4(1), pp.17-22, 2017

     

    Published 2016

    • Compressed sensing and sparsity in photoacoustic tomography
      M. Haltmeier, T. Berer, S. Moon and P. Burgholzer
      J Opt 18(11), 2016
    • Sparsifying transformations of photoacoustic signals enabling compressed sensing algorithms
      P. Burgholzer, M. Sandbichler, F. Krahmer, T. Berer, M. Haltmeier
      Proc. SPIE 9708:970828, 2016

     

    Published 2015

    • Mapping molecules in scanning far-field fluorescence nanoscopy
      T. Haisen, J. Keller, M. Haltmeier, S.K. Saka, J. Schmied, F. Opazo, P. Tinnefeld, A. Munk, S.W Hell
      Nat Commun, 6, 7977, 2015
    • Single-stage reconstruction algorithm for quantitative photoacoustic tomography
      M. Haltmeier, L. Neumann, S. Rabanser
      Inverse Probl 31(6):065005, 2015 [pdf pdf button]

     

    Published 2014

    • Graphical Lasso Granger method with 2-levels-thresholding for recovering causality networks
      S. Pereverzyev Jr., K. Hlavackova-Schindler
      Chapter in C. Pötzsche, C. Heuberger, B. Kaltenbacher, F. Rendl: System Modeling and Optimization 443, pp.220-229, 2014 [pdf pdf button]

    • Deblurring algorithms accounting for the finite detector size in photoacoustic tomography
      H. Roitner, M. Haltmeier, T. Berer, H. Grün, D.P. O'Leary, R. Nuster, G. Paltauf, P. Burgholzer
      J Biomed Opt 19(5):056011, 2014
    • Parameter identification for an advanced material model for intact rock
      D. Unteregger, G. Hofstetter, M. Haltmeier, A. Ostermann
      Chapter 37 in M. A, Hicks, R. B, J, Brinkgreve, A. Rohe (Editors): Proc. NUMGE 2014, pp.215-220, 2014
    • Spatial over-sampling and its influence on spatial resolution for photoacoustic tomography with finite sized detectors
      P. Burgholzer, H. Roitner, T. Berer, H. Grün, R. Nuster, G. Paltauf, M. Haltmeier
      Proc. SPIE 8943:89432K, 2014

     

    Published 2013

    • Deconvolution algorithms for photoacoustic tomography to reduce blurring caused by finite sized detectors
      P. Burgholzer, H. Roitner, T. Berer, H. Grün, D.P. O'Leary, R. Nuster, G. Paltauf, M. Haltmeier
      Proc. SPIE 8581:858137, 2013

     

    2012

    • Small frequency approximation of (causal) dissipative pressure waves
      R. Kowar
      Proc. The Fifth Symposium on Fractional Differentiation and Its Applications 2012 [arxiv.org]

     

    2011

    • Photoacoustic tomography with integrating fiber-based annular detectors
      H. Gruen, H. Altmisdoert, T. Berer, G. Paltauf, G. Zangerl, M.Haltmeier, P. Burgholzer
      Proc. SPIE 7968:79680B, 2011

     

    2010

    • Spatial resolution in photoacoustic tomography: effects of detector size and detector bandwidth
      M. Haltmeier, G. Zangerl
      Inverse Probl. 26(12):125002, 2010
    • Integral equation models for thermoacoustic imaging of acoustic dissipative tissue
      R. Kowar
      Inverse Probl 26, 2010 [arxiv.org]
    • Using a phase contrast imaging method in photoacoustic tomography
      R. Nuster, G. Zangerl, O. Scherzer, M. Haltmeier, G. Paltauf
      Proc. SPIE 7564:75640Q, 2010
    • (Habilitation thesis) Mathematical methods in photoacoustic image reconstruction
      M. Haltmeier
      Habilitation Thesis. University Vienna, iv+244 pages, 2010

     

    2009

    • Causality analysis of waves and wave equations obeying attenuation
      R. Kowar
      Research Report: Network FWF S105: Photoacoustic Imaging in Medicine and Biology, 2009, 6, January [arxiv.org]
    • Influence of bandwidth and detector size to the resolution of photoacoustic tomography
      M. Haltmeier, O. Scherzer, G. Zangerl
      Proc. MATHMOD 09 Vienna, ARGESIM Report no. 35, 2009

     

    2008

    • Optimizing image resolution in three-dimensional photoacoustic tomography with line detectors
      G. Paltauf, R. Nuster, K. Passler, M. Haltmeier, P. Burgholzer
      Proc. SPIE 6856:685621, 2008
    • Photoacoustic tomography of heterogeneous media using a model-based time reversal method
      H. Gruen, R. Nuster, G. Paltauf, M. Haltmeier, P. Burgholzer
      Proc. SPIE 6856:685620, 2008

     

    2007

    • Experimental evaluation of reconstruction algorithms for limited view photoacoustic tomography with line detectors
      G. Paltauf, R. Nuster, M. Haltmeier, P. Burgholzer
      Inverse Probl 23(6), pp.81-94, 2007
    • Temporal back-projection algorithms for photoacoustic tomography with integrating line detectors
      P. Burgholzer, J. Bauer-Marschallinger, H. Gruen, M. Haltmeier, G. Paltauf
      Inverse Probl 23(6), pp.65-80, 2007
    • Photoacoustic computed tomography using a Mach-Zehnder interferometer as acoustic line detector
      G. Paltauf, R. Nuster, M. Haltmeier, P. Burgholzer
      Appl Opt 46, pp.3352-3358, 2007
    • Three-dimensional photoacoustic tomography using acoustic line detectors
      G. Paltauf, R. Nuster, P. Burgholzer, M. Haltmeier
      Proc. SPIE 6437:64370N, 2007
    • Compensation of acoustic attenuation for high-resolution photoacoustic imaging with line detectors
      P. Burgholzer, H. Gruen, M. Haltmeier, R. Nuster, G. Paltauf
      Proc. SPIE 6437:643724, 2007
    • Photoacoustic tomography using a fiber based Fabry-Perot interferometer as an integrating line detector and image reconstruction by model-based time reversal method
      H. Gruen, G. Paltauf, M. Haltmeier, P. Burgholzer
      Proc. SPIE 6631:663107, 2007
    • Two-dimensional image reconstruction for photo-acoustic tomography with line detectors
      G. Paltauf, R. Nuster, M. Haltmeier, P. Burgholzer
      Proc. SPIE 6631:663104, 2007

     

    2006

    • Thermoacoustic tomography using a fiber-based Fabry-Perot interferometer as an integrating line detector
      P. Burgholzer, C. Hofer, and G. J. Matt, G. Paltauf, M. Haltmeier, O. Scherzer
      Proc. SPIE 6086:60861N, 2006
    • Reconstruction of transducer pressure fields from schlieren data
      R. Kowar
      Proc. ECMI 2006, 2006
    • Mathematical challenges arising in thermoacoustic tomography with line detectors
      M. Haltmeier, T. Fidler
      Technical report, 2006 [arxiv.org]
    • Tikhonov and iterative regularization methods for embedded inverse problems
      M. Haltmeier, O. Scherzer, A. Leitao
      Technical report, 2006
    • (PhD Thesis) Fast direct reconstruction algorithms for high resolution thermoacoustic CT
      M. Haltmeier
      University Innsbruck, vii+113 pages, 2006

     

    2005

    • Estimation of the density, the wave speed and the acoustic impedance function in ultrasound imaging
      R. Kowar
      Inverse Probl 21, pp.93-112, 2005
    • Thermoacoustic tomography using optical line detection
      G. Paltauf, P. Burgholzer, M. Haltmeier, O. Scherzer
      Proc. SPIE 5864, pp.02-08, 2005
    • Thermoacoustic tomography using integrating detectors
      P. Burgholzer, C. Hofer, G. Paltauf, M. Haltmeier, O. Scherzer
      Proc. SPIE 5864, pp.03-12, 2005

     

    2004

    • Numerical estimation of the acoustic impedance function of nonhomogeneous media
      R. Kowar
      Proc. ECCOMAS 2004, 2004