Submitted

• Recovering the Initial Data of the Wave Equation from Neumann Traces
  F. Dreier, M. Haltmeier
  Submitted, 2020 [pdf][arxiv.org]

• Multi-Scale factorization of the wave equation with application to compressed sensing photoacoustic tomography
  G. Zangerl, M. Haltmeier
  Submitted, 2020 [pdf ][arxiv.org]
  

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

• Sparse aNETT for solving inverse problems with deep learning
  D. Obmann, L. Nguyen, J. Schwab, M. Haltmeier
  Submitted, 2020 [pdf ][arxiv.org]

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

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

• Neural networks-based regularization for large-scale medical image reconstruction
  A. Kofler, M. Haltmeier, T. Schaeffter, M. Kachelriess, M. Dewey, C. Wald and C. Kolbitsch
  Submitted, 2019 [pdf ][arxiv.org]

• Sparse regularization of inverse problems by biorthogonal frame thresholding
  J. Frikel, M. Haltmeier
  Submitted, 2019 [pdf ] [arxiv.org]

• Real-time photoacoustic projection imaging using deep learning
  J. Schwab, S. Antholzer, R. Nuster and M. Haltmeier
  Submitted, 2018 [pdf ] [video-1] [video-2] [video-3] [video-4] [arxiv.org]

Published 2020

• Sparse synthesis regularization with deep neural networks
  D. Obmann, J. Schwab, M. Haltmeier
  IEEE SampTA (9030953), pp.1-5, 2020 [pdf ] [arxiv.org]
  

• Projection-Based 2.5D U-net architecture for fast volumetric segmentation
  C. Angermann, M. Haltmeier, R. Steiger, S. Pereverzyev, E. Gizewski
  IEEE SampTA (9030861), pp.1-5, 2020 [pdf ] [arxiv.org]

• 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
  

• Superiorized regularization of inverse problems
  A. Gibali, M. Haltmeier
  J Appl Numer Optim 2(1), pp.63-70, 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

• Explicit inversion formulas for the two-dimensional wave equation from Neumann traces
  F. Dreier, M. Haltmeier
  SIAM J Imaging Sci 13(2), p.589–608, 2020 [pdf ] [arxiv.org]

• 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 ]

• NETT: solving inverse problems with deep neural networks
  H. Li, J. Schwab, S. Antholzer, M. Haltmeier
  Invers Probl, 2020 [pdf ] [arxiv.org]

• Big in Japan: Regularizing networks for solving inverse problems
  J. Schwab, S. Antholzer, M. Haltmeier
  J Math Imaging Vis 62, pp.445-455,  2020 [pdf ] [arxiv.org]

Published 2019

• Analysis of the block coordinate descent method for linear Ill-posed problems
  S. Rabanser, L. Neumann, M. Haltmeier
  SIAM J Imaging Sci 12(4), pp.1808-1832,  2019 [pdf ] [arxiv.org]

• Random 2.5D U-net for Fully 3D Segmentation
  C. Angermann, M. Haltmeier
  MLMECH, CVII-STENT, Computer Science Vol. 11794, Springer, Cham, 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]

• Reconstruction algorithms for photoacoustic tomography in heterogeneous damping media
  M. Haltmeier, L.V. Nguyen
  J Math Imaging Vis 61(7), pp.1007-1021, 2019 [pdf ] [arxiv.org]

• Photoacoustic tomography with direction dependent data: an exact series reconstruction approach
  G. Zangerl, S. Moon, M. Haltmeier
  Inverse Probl 35(11), 2019 [pdf ] [arxiv.org]
  
  
• Douglas-Rachford algorithm for magnetorelaxometry imaging using random and deterministic activations
  M. Haltmeier, G. Zangerl, P. Schier, D. Baumgarten
  Int J Appl Electrom 60(1), pp.63-78, 2019 [arxiv.org]
  
  
• Deep learning for photoacoustic tomography from sparse data
  S. Antholzer, M. Haltmeier, J. Schwab
  Inverse Probl Sci En 27(7), pp.987-1005, 2019 [pdf ] [arxiv.org]

• Operator learning approach for the limited view problem in photoacoustic tomography
  F. Dreier, S. Pereverzyev Jr., M. Haltmeier
  Comput Meth Appl Math 19(4), pp.749-764, 2019 [pdf] [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 photoacousic tomography
  A. Antholzer, J. Schwab, J. Bauer-Marschallinger, P. Burgholzer, M. Haltmeier
  Proc. SPIE, Vol. 10878, 2019

• Online and stable learning of analysis operators
  M. Sandbichler, K. Schnass
  IEEE Trans Signal Process 67(01), pp.41-53, 2019 [pdf ] [arxiv.org]

• 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 ] [arxiv.org]

• Deep null space learning for inverse problems: convergence analysis and rates
  J. Schwab, S. Antholzer, M. Haltmeier
  Inverse Probl 35(02), pp.13, 2019 [pdf ] [arxiv.org]

• Image based fashion product recommendation with deep learning
  H. Tuinhof, C. Pirker, M. Haltmeier
  Machine Learning, Optimization, and Data Science, 4th International Conference, Volterra, Italy, 2018, Revised Selected Papers 2019 [pdf ] [arxiv.org]

Published 2018

• Variational regularization of the weighted conical Radon transform
  M. Haltmeier, D. Schiefeneder
  Inverse Probl 34(12), pp.17, 2018 [pdf ] [arxiv.org]

• Convergence radius and sample complexity of ITKM algorithms for dictionary learning
  K. Schnass
  Appl Comput Harmon A 45(1), pp.22-58, 2018 [pdf ]

• 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 ] [arxiv.org]

• A U-Nets cascade for sparse view computed tomography
  A. Kofler, M. Haltmeier, C. Kolbitsch, M. Kachelrieß, M. Dewey
  Proc. MLMIR 2018, Lecture Notes in Computer Science, Vol. 11074, pp.91-99, Springer, Cham

• Total variation minimization compressed sensing
  F. Krahmer, C. Kruschel, M. Sandbichler
  Applied Numerical Harmonic Analysis, pp.333-358, 2018

• Photoacoustic image reconstruction via deep learning
  S. Antholzer, M. Haltmeier, R. Nuster, J. Schwab
  Proc. SPIE 10494:104944U, 2018 [pdf ]

• Stochastic proximal gradient algorithms for multi-source quantitative photoacoustic tomography
  S. Rabanser, L. Neumann, M. Haltmeier
  Entropy, 20(2):121, 2018 [pdf ] [arxiv.org]

• The averaged Kaczmarz iteration for solving inverse problems
  H. Li, M. Haltmeier
  SIAM J Imaging Sci 11(1), pp.618–642, 2018 [pdf ] [arxiv.org]

• Efficient regularization with wavelet sparsity constraints in PAT
  J. Frikel, M. Haltmeier
  Inverse Probl 34(2):024006, pp.28, 2018 [pdf ] [arxiv.org]

• Analysis of the linearized problem of quantitative photoacoustic tomography
  M. Haltmeier, L. Neumann, L. V. Nguyen, S. Rabanser
  SIAM J Appl Math 78(1), pp.457–478, 2018. [pdf ] [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

• A Galerkin least squares approach for photoacoustic tomography
  J. Schwab, S. Pereverzyev Jr., M. Haltmeier
  SIAM J Numer Anal 56(1), pp.160–184, 2018 [pdf ] [arxiv.org]

Published 2017

• Dictionary learning from incomplete data for efficient image restoration
  V. Naumova, K. Schnass
  25^th EUSIPCO Kos, pp.1425-1429, 2017 [pdf ] [arxiv.org]

• Iterative methods for photoacoustic tomography in attenuating acoustic media
  M. Haltmeier, R. Kowar, L. V. Nguyen
  Inverse Probl 33(11):115009, 2017 [pdf ] [arxiv.org]

• Inversion of the attenuated V-Line transform with vertices on the circle
  M. Haltmeier, S. Moon, D. Schiefeneder
  IEEE Trans Comput Imaging Vol. 3(4): 853-863, 2017 [arxiv.org]

• 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 ]

• Multi-penalty regularization for detecting relevant variables
  K. Hlavackova-Schindler, V. Naumova, S. Pereverzyev Jr.
  Recent Applications of Harmonic Analysis to Function Spaces, Differential Equations, and Data Science,889-916. Birkhäuser, 2017 [pdf ]

• Analytic inversion of a conical Radon transform arising in application of compton cameras on the cylinder
  S. Moon, M. Haltmeier
  SIAM J Imaging Sci 10(2), pp.535–557, 2017 [arxiv.org]

• The Radon transform over cones with vertices on the sphere and orthogonal axes
  D. Schiefeneder, M. Haltmeier
  SIAM  J Appl Math 77(4), pp.1335-1351, 2017 [arxiv.org]

• Analysis of iterative methods in photoacoustic tomography with variable sound speed
  M. Haltmeier, L. V. Nguyen
  SIAM J Imaging Sci 10(2), 2017 [arxiv.org]

• Compressed sensing in photoacoustic imaging and application for planar detection geometries
  T. Berer, P. Burgholzer, M. Haltmeier
  Proc. SPIE 10064:100642, 2017
  

• A parameter choice strategy for the inversion of multiple observations
  C. Gerhards, S. Pereverzyev Jr., P. Tkachenko
  Adv Comput Math 43(1), pp.101-112, 2017 [pdf ]

• The spherical Radon transform with centers on cylindrical surfaces
  M. Haltmeier, S. Moon
  J Math Anal Appl 448(1), pp.567-579,  2017 [arxiv.org]

• 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

• Sampling conditions for the circular Radon transform
  M. Haltmeier
  IEEE Trans Image Process 25(6), pp.2910-2919, 2016 [pdf]

• Granger causality for Ill-Posed problems: ideas, methods, and application in life sciences
  K. Hlavackova-Schindler, V. Naumova, S. Pereverzyev Jr.
  Statistics and Causality: Methods for Applied Empirical Research, pp.249-276. Wiley, 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

• A novel compressed sensing scheme for photoacoustic tomography
  M. Sandbichler, F. Krahmer, T. Berer, P. Burgholzer, M. Haltmeier
  SIAM J Appl Math 75(6), pp.2475-2494, 2015 [pdf ]

• 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

• Aggregation of regularized solutions from multiple observation models
  J. Chen, S. Pereverzyev Jr., Y. Xu
  Inverse Probl 31(7):075005 , 2015 [pdf ]

• Single-stage reconstruction algorithm for quantitative photoacoustic tomography
  M. Haltmeier, L. Neumann, S. Rabanser
  Inverse Probl 31(6):065005, 2015 [pdf ]

• Causality analysis of the fractional state and wave equations based on fractional Laplacians
  R. Kowar
  Wave Motion 58, pp.244-258, 2015 [arxiv.org]
  

• The universal back-projection formula for spherical means and the wave equation on certain quadric hypersurfaces
  M. Haltmeier, S. Pereverzyev Jr.
  J Math Anal Appl 429(1), pp.366-382, 2015 [pdf ]

• Recovering a function from circular means or wave data on the boundary of parabolic domains
  M. Haltmeier, S. Pereverzyev Jr.
  SIAM J Imaging Sci 8(1), pp.592-610, 2015 [pdf ]

• Lasso Granger causal models: some strategies and their efficiency for gene expression regulatory networks
  K. Hlavackova-Schindler, S. Pereverzyev Jr.
  Chapter in T. v. Guy, M.Kárný, D. H. Wolpert (Editors): Decision Making: Uncertainty, Imperfection, Deliberation and Scalability, 538, pp.91-117, Springer, 2015.
  

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 ]

• Introduction to the mathematics of computed tomography
  M. Haltmeier, S. Pereverzyev Jr.
  Internat Math Nachrichten 226, pp.29-51, 2014 [pdf ]

• 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

• Exact reconstruction formula for the spherical Mean-Radon transform on ellipsoids
  M. Haltmeier
  Inverse Probl 30(10):105006, 2014 [pdf ]

• On time reversal in photoacoustic tomography for tissue similar to water
  R. Kowar
  SIAM J Imaging Sci 7(1), pp.509-527, 2014 [arxiv.org] [pdf ]

• Aggregated motion estimation for real-time MRI reconstruction
  H. Li, M. Haltmeier, S. Zhang, J. Frahm, A. Munk
  Magn Reson Med 72(4), pp.1039-1048, 2014 [arxiv.org]

• Time reversal for photoacoustic tomography based on the wave equation of Nachman, Smith and Waag.
  R. Kowar
  Phys Rev E Stat Nonlin Soft Matter Phys 89(2):023203, 2014, [arxiv.org] [pdf ]

• Extreme value analysis of empirical frame coefficients and implications for denoising by soft-thresholding
  M. Haltmeier, A. Munk
  Appl Comput Harmon Anal 36(3), pp.434-460 2014 [arxiv.org] [pdf ]

• Universal inversion formulas for recovering a function from spherical means
  M. Haltmeier
  SIAM J Math Anal 46(1), pp.214-232, 2014 [arxiv.org] [pdf ]

• Exact reconstruction formulas for a Radon transform over cones
  M. Haltmeier
  Inverse Probl 30(3):035001, 2014 [arixv.org] [pdf ]

• 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

• Credid scorecard for corporate clients based on industries
  S. Janicijevic, Z. Luzanin, S. Pereverzyev Jr., I. Stojkovska, A. Tepavcevic.
  Proc. 99^th European Study Group with Industry, 2014

Published 2013

• Inversion of circular means and the wave equation on convex planar domain
  M. Haltmeier
  Comput Math Appl 65(3), pp.1025-1036. 2013 [arxiv.org] [pdf ]

• Stable Signal Reconstruction via \(l^1\)-minimization in Redundant, Non-Tight Frames
  M. Haltmeier
  IEEE Trans Signal Process 61(2), pp.420-426, 2013

• Analysis of a causal diffusion model and its backwards diffusion problem
  R. Kowar
  J Math Anal Appl 400(1), pp.222-238, 2013 [arxiv.org]

• Block-sparse analysis regularization of ill-posed problems via \(l^{1,2}\)-minimization
  M. Haltmeier
  Proc. MMAR 2013, pp.520-523, 2013

• Aggregated motion estimation for parallel Real-Time MRI
  H. Li, M. Haltmeier, S. Zhang, J. Frahm, A. Munk
  Proc. 59^th ISI World Statistics Conference, 2013 [pdf ]

• 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]

• Attenuation models in photoacoustics
  R. Kowar, O. Scherzer
  Chapter in H. Ammari (Editor); Mathematical Modeling in Biomedical Imaging II: 85-130, 2012 [arxiv.org]

• On the causality of real-valued semigroups and diffusion
  R. Kowar
  Math Methods in the Appl Sci 35(2), pp.207-227, 2012 [arxiv.org]

2011

• The residual method for regularizing ill-posed problems
  M. Grasmair, M. Haltmeier, O. Scherzer
  Appl Math Comput 218(6), pp.2693-2710, 2011 [arxiv.org]

• A mollification approach for inverting the spherical mean Radon transform
  M. Haltmeier
  SIAM J Appl Math 71(5), pp.1637-1652, 2011

• Inversion formulas for a cylindrical Radon transform
  M. Haltmeier
  SIAM J Imaging Sci 4(3), pp.789-806, 2011

• Necessary and sufficient conditions for linear convergence of \(l^1\)-Regularization
  M. Grasmair, M. Haltmeier, O. Scherzer
  Comm Pure Appl Math 64(2), pp.161-182, 2011

• Causality analysis of frequency-dependent wave attenuation
  R. Kowar, and O. Scherzer and X. Bonnefond
  Math Methods in the Appl Sci 34(1), pp.108-124, 2011 [arxiv.org]

• 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

• Real-valued semigroups and (causal) diffusion
  R. Kowar
  AIP Conf Proc 1389, pp.886-888, 2011 (3 pages)

2010

• Sparsity in inverse geophysical problems
  M. Grasmair, M. Haltmeier, O. Scherzer
  Handbook of Geomathematics, pp.763-764. Springer, 2010

• Spatial resolution in photoacoustic tomography: effects of detector size and detector bandwidth
  M. Haltmeier, G. Zangerl
  Inverse Probl. 26(12):125002, 2010

• Full field detection in photoacoustic tomography
  R. Nuster, G. Zangerl, M. Haltmeier, G. Paltauf
  Opt Express 18(6), pp.6288-6299, 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

• (Book) Variational methods in imaging
  O. Scherzer, M. Grasmair, H. Grossauer, M. Haltmeier, F. Lenzen
  Applied Mathematical Sciences 196, Springer, New York, 2009 [Google books]

• Photoacoustic tomography with integrating area and line detectors
  G. Paltauf, R. Nuster, M. Haltmeier, P. Burgholzer
  Photoacoustic imaging and spectroscopy, CRC Press, 2009

• Frequency domain reconstruction in photo- and thermoacoustic tomography with line detectors
  M. Haltmeier
  Math Models Methods Appl Sci 19(2), pp.283-306, 2009

• On regularization methods of EM-Kaczmarz type
  M. Haltmeier, A. Leitao, E. Resmerita
  Inverse Probl 25(7):075008, 2009 [arxiv.org]

• Exact series reconstruction in photoacoustic tomography with circular integrating detectors
  G. Zangerl, M. Haltmeier, O. Scherzer
  Commun Math Sci 7(3), pp.665-678, 2009 [arxiv.org]

• A reconstruction algorithm for photoacoustic imaging based on the nonuniform FFT
  M. Haltmeier, O. Scherzer, G. Zangerl
  IEEE Trans Med Imag 28(3), pp.1727-1735, 2009 [arxiv.org]

• Circular integrating detectors in photo and thermoacoustic tomography
  G. Zangerl, M. Haltmeier, O. Scherzer
  Inverse Probl Sci Eng 17(1), pp.133-142, 2009

• Convergence analysis of a block iterative version of the loping Landweber-Kaczmarz iteration
  M. Haltmeier
  Nonlinear Anal Theory Methods Appl 71(12), pp.2912-2919, 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

• Sparse regularization with \(l^q\) penalty term
  M. Grasmair, M. Haltmeier, O. Scherzer
  Inverse Probl 24(5):055020, 2008 [arxiv.org]

• On steepest-descent Kaczmarz methods for regularizing systems of nonlinear ill-posed equations
  A. De Cesaro, M. Haltmeier, A. Leitao, O. Scherzer
  Appl Math Comput 202, pp.596-607, 2008 [arxiv.org]

• 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

• Inversion of spherical means and the wave equation in even dimensions
  D. Finch, M. Haltmeier, Rakesh
  SIAM J Appl Math 68(2), pp.392-412, 2007 [arxiv.org]

• Kaczmarz methods for regularizing nonlinear ill-posed equations I: convergence analysis
  M. Haltmeier, A. Leitao, O. Scherzer
  Inverse Probl Imaging 1(2), pp.289-298, 2007  [pdf ]

• Kaczmarz methods for regularizing nonlinear ill-posed equations II: Applications
  M. Haltmeier, R. Kowar, A. Leitao, O. Scherzer
  Inverse Probl Imaging 1(3), pp.507-523, 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

• Thermoacoustic tomography and the circular Radon transform: exact inversion formula
  M. Haltmeier, O. Scherzer, P. Burgholzer, R. Nuster, G. Paltauf
  Math Models Methods Appl Sci 17(4), pp.635-655, 2007

• Exact and approximate imaging methods for photoacoustic tomography using an arbitrary detection surface
  P. Burgholzer, G. J. Matt, M. Haltmeier, G. Paltauf
  Phys Rev E Stat Nonlin Soft Matter Phys 75(4):046706, 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

• Thermoacoustic imaging using time reversal
  H. Gruen, C. Hofer, M. Haltmeier, G. Paltauf, P. Burgholzer
  International Congress on Ultrasonics, Paper ID 1542, 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

• Computer aided location of avalanche victims with ground penetrating radar mounted on a helicopter
  M. Haltmeier, R. Kowar, O. Scherzer
  Proc. 30^th Workshop of the Austrian Association for Pattern Recognition, pp.65-74, 2006 [pdf ]

• Thermoacoustic tomography - ultrasound attenuation artifacts
  S. K. Patch, M. Haltmeier
  IEEE Nuclear Science Symposium Conference Record 4, pp.2604-2606, 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

• Rapid location of avalanche victims with ground penetrating radar
  M. Haltmeier, R. Kowar
  ECMI-Newsletter 39, pp.31-33, 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

• Filtered backprojection for thermoacoustic computed tomography in spherical geometry
  M. Haltmeier, T. Schuster, O. Scherzer
  Mathematical Methods in the Applied Sciences 28(16), pp.1919-1937, 2005  [pdf ]

• Thermoacoustic tomography with integrating area and line detectors
  P. Burgholzer, C. Hofer, G. Paltauf, M. Haltmeier, O. Scherzer
  IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control 52(9), pp.1577-1583, 2005

• Thermoacoustic tomography using integrating line detectors
  P. Burgholzer, C. Hofer, G. Paltauf, R. Nuster, M. Haltmeier, O. Scherzer
  IEEE Ultrasonics Symposium 2005 Proceedings, pp.166-169, 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

• Thermoacoustic computed tomography with large planar receivers
  M. Haltmeier
  ECMI-Newsletter 37, pp.31-33, 2005

2004

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

• Thermoacoustic computed tomography with large planar receivers
  M. Haltmeier, O. Scherzer, P. Burgholzer, G. Paltauf
  Inverse Probl 20(5), pp.1663-1673, 2004  [pdf ]