Prof. Markus Haltmeier Profile

Prof. Markus Haltmeier

Professor at Univ Innsbruck

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Author

Publications (29)

SPIE Journal Paper | 22 April 2024 Open Access

Design, implementation, and analysis of a compressed sensing photoacoustic projection imaging system

Markus Haltmeier, Matthias Ye, Karoline Felbermayer, Florian Hinterleitner, Peter Burgholzer

JBO, Vol. 29, Issue S1, S11529, (April 2024) https://doi.org/10.1117/12.10.1117/1.JBO.29.S1.S11529

KEYWORDS: Matrices, Design, Sensors, Image restoration, Compressed sensing, Biological research, Imaging systems, Signal detection, Photoacoustic spectroscopy, Transform theory

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Proceedings Article | 13 June 2022 Presentation

Super-resolution thermographic imaging

Peter Burgholzer, Gregor Thummerer, Guenther Mayr, Markus Haltmeier

Proceedings Volume PC12109, (2022) https://doi.org/10.1117/12.2618390

KEYWORDS: Super resolution, Light scattering, Laser scattering, Ultrasonography, Thermography, Reconstruction algorithms, Natural surfaces, Microscopy, Laser tissue interaction, Infrared cameras

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Proceedings Article | 9 December 2021 Paper

Sampling and resolution in sparse view photoacoustic tomography

Markus Haltmeier, Daniel Obmann, Florian Dreier, Stephan Antholzer, Karoline Felbermayer, Florian Hinterleitner, Peter Burgholzer

Proceedings Volume 11923, 119230A (2021) https://doi.org/10.1117/12.2615869

KEYWORDS: Acquisition tracking and pointing, Sensors, Spatial resolution, Photoacoustic tomography, Signal detection, Point spread functions, Linear filtering, Data acquisition, Acoustics, Signal attenuation

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Proceedings Article | 9 December 2021 Paper

Relaxed data-consistency for limited bandwidth photoacoustic tomography

Daniel Obmann, Markus Haltmeier

Proceedings Volume 11923, 1192307 (2021) https://doi.org/10.1117/12.2615853

KEYWORDS: Data modeling, Transducers, Photoacoustic tomography, Acquisition tracking and pointing, Point spread functions, Bandpass filters, Visibility, Reconstruction algorithms, Optical imaging, Visualization

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Proceedings Article | 5 March 2021 Presentation + Paper

Photoacoustic reconstruction from photothermal measurements

Peter Burgholzer, Gregor Thummerer, Guenther Mayr, Markus Haltmeier

Proceedings Volume 11642, 116421S (2021) https://doi.org/10.1117/12.2585358

KEYWORDS: Photoacoustic spectroscopy, Signal attenuation, Acoustics, Temperature metrology, Spatial resolution, Photoacoustic tomography, Inverse problems, Inspection, Infrared cameras, Image restoration

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Proceedings Article | 3 March 2020 Paper

Breaking the resolution limit in photoacoustic imaging using positivity and sparsity

Peter Burgholzer, Johannes Bauer-Marschallinger, Mike Hettich, Markus Haltmeier

Proceedings Volume 11240, 112403Y (2020) https://doi.org/10.1117/12.2543515

KEYWORDS: Signal attenuation, Acoustics, Tissues, Spatial resolution, Photoacoustic imaging, Image resolution, Transducers, Tissue optics, Semiconducting wafers, Thermodynamics

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Proceedings Article | 27 February 2019 Paper

Photoacoustic image reconstruction from full field data in heterogeneous media

Markus Haltmeier, Gerhard Zangerl, Linh Nguyen, Robert Nuster

Proceedings Volume 10878, 108783D (2019) https://doi.org/10.1117/12.2508541

KEYWORDS: Image restoration, Radon transform, Reconstruction algorithms, Acquisition tracking and pointing, Photoacoustic tomography, Acoustics

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Proceedings Article | 27 February 2019 Paper

NETT regularization for compressed sensing photoacoustic tomography

Stephan Antholzer, Johannes Schwab, Johnnes Bauer-Marschallinger, Peter Burgholzer, Markus Haltmeier

Proceedings Volume 10878, 108783B (2019) https://doi.org/10.1117/12.2508486

KEYWORDS: Compressed sensing, Convolution, Photoacoustic tomography, Sensors, Reconstruction algorithms, Inverse problems, Neural networks, Image restoration, Network architectures

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Proceedings Article | 27 February 2019 Paper

Learned backprojection for sparse and limited view photoacoustic tomography

Johannes Schwab, Stephan Antholzer, Markus Haltmeier

Proceedings Volume 10878, 1087837 (2019) https://doi.org/10.1117/12.2508438

KEYWORDS: Sensors, Acquisition tracking and pointing, Photoacoustic tomography, Reconstruction algorithms, Image restoration, Detection and tracking algorithms, Photoacoustic spectroscopy, Distance measurement, Acoustics, 3D image reconstruction

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Proceedings Article | 27 February 2019 Paper

Deep Learning of truncated singular values for limited view photoacoustic tomography

Johannes Schwab, Stephan Antholzer, Robert Nuster, Günther Paltauf, Markus Haltmeier

Proceedings Volume 10878, 1087836 (2019) https://doi.org/10.1117/12.2508418

KEYWORDS: Acquisition tracking and pointing, Image restoration, Photoacoustic tomography, Inverse problems, Photoacoustic spectroscopy, Neural networks, Acoustics, Sensors, Network architectures, Tomography

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Proceedings Article | 19 February 2018 Paper

Photoacoustic image reconstruction via deep learning

Stephan Antholzer, Markus Haltmeier, Robert Nuster, Johannes Schwab

Proceedings Volume 10494, 104944U (2018) https://doi.org/10.1117/12.2290676

KEYWORDS: Image restoration, Acquisition tracking and pointing, Reconstruction algorithms, Sensors, Acoustics, Network architectures, Photoacoustic spectroscopy, Photoacoustic tomography, Neural networks, Convolution

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Proceedings Article | 1 August 2017 Paper

Super-resolution photoacoustic microscopy using joint sparsity

P. Burgholzer, M. Haltmeier, T. Berer, E. Leiss-Holzinger, T. Murray

Proceedings Volume 10415, 1041506 (2017) https://doi.org/10.1117/12.2286281

KEYWORDS: Super resolution, Photoacoustic microscopy, Speckle pattern, Photoacoustic spectroscopy

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Proceedings Article | 15 March 2017 Presentation + Paper

Photoacoustic super-resolution microscopy using blind structured speckle illumination

P. Burgholzer, T. Murray, M. Haltmeier, E. Leiss-Holzinger, T. Berer

Proceedings Volume 10064, 100642H (2017) https://doi.org/10.1117/12.2250939

KEYWORDS: Speckle pattern, Photoacoustic spectroscopy, Speckle, Ultrasonography, Reconstruction algorithms, Super resolution, Geometrical optics, Microscopy, Transducers, Super resolution microscopy, Spatial resolution, Point spread functions, Photoacoustic microscopy, Acoustics

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Proceedings Article | 3 March 2017 Presentation + Paper

Compressed sensing in photoacoustic imaging and application for planar detection geometries

Thomas Berer, Peter Burgholzer, Markus Haltmeier

Proceedings Volume 10064, 100642I (2017) https://doi.org/10.1117/12.2250857

KEYWORDS: Compressed sensing, Photoacoustic imaging, Photoacoustic tomography, Ultrasonics, Transform theory, Computer simulations, Spatial resolution, Image restoration, Matrices, Photoacoustic spectroscopy, Data acquisition, Sensors, Binary data, Reconstruction algorithms

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Proceedings Article | 15 March 2016 Presentation + Paper

Sparsifying transformations of photoacoustic signals enabling compressed sensing algorithms

P. Burgholzer, M. Sandbichler, F. Krahmer, T. Berer, M. Haltmeier

Proceedings Volume 9708, 970828 (2016) https://doi.org/10.1117/12.2209301

KEYWORDS: Compressed sensing, Sensors, Signal detection, Photoacoustic spectroscopy, Tomography, Photoacoustic tomography, Image restoration, Fiber optics sensors, Image sensors, Ultrasonics, Photoacoustic imaging, 3D image processing, Acoustics

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SPIE Journal Paper | 22 May 2014 Open Access

Deblurring algorithms accounting for the finite detector size in photoacoustic tomography

Heinz Roitner, Markus Haltmeier, Robert Nuster, Dianne O’Leary, Thomas Berer, Guenther Paltauf, Hubert Grün, Peter Burgholzer

JBO, Vol. 19, Issue 05, 056011, (May 2014) https://doi.org/10.1117/12.10.1117/1.JBO.19.5.056011

KEYWORDS: Sensors, Reconstruction algorithms, Detection and tracking algorithms, Deconvolution, Signal detection, Photoacoustic tomography, Acoustics, Computer simulations, Photoacoustic spectroscopy, Image restoration

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Proceedings Article | 3 March 2014 Paper

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

Proceedings Volume 8943, 89432K (2014) https://doi.org/10.1117/12.2039591

KEYWORDS: Sensors, Reconstruction algorithms, Deconvolution, Signal detection, Detection and tracking algorithms, Photoacoustic tomography, Acoustics, Spatial resolution, Detector arrays, Convolution

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Proceedings Article | 4 March 2013 Paper

Deconvolution algorithms for photoacoustic tomography to reduce blurring caused by finite sized detectors

Peter Burgholzer, Heinz Roitner, Thomas Berer, Hubert Grün, D. O'Leary, R. Nuster, G. Paltauf, M. Haltmeier

Proceedings Volume 8581, 858137 (2013) https://doi.org/10.1117/12.2003889

KEYWORDS: Sensors, Signal detection, Detection and tracking algorithms, Reconstruction algorithms, Deconvolution, Photoacoustic tomography, Acoustics, Spherical lenses, Wave propagation, Detector arrays

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Proceedings Article | 25 March 2011 Paper

Photoacoustic tomography with integrating fiber-based annular detectors

H. Grün, H. Altmisdört, T. Berer, G. Paltauf, G. Zangerl, M. Haltmeier, P. Burgholzer

Proceedings Volume 7968, 79680B (2011) https://doi.org/10.1117/12.877980

KEYWORDS: Sensors, Photoacoustic tomography, Tomography, Image restoration, Signal detection, Spatial resolution, Glasses, Photoacoustic imaging, Absorption, Photoacoustic spectroscopy

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Proceedings Article | 24 February 2010 Paper

Using a phase contrast imaging method in photoacoustic tomography

R. Nuster, G. Zangerl, M. Haltmeier, O. Scherzer, G. Paltauf

Proceedings Volume 7564, 75640Q (2010) https://doi.org/10.1117/12.842348

KEYWORDS: Acoustics, Radon transform, Photoacoustic tomography, Sensors, Phase contrast, CCD cameras, Wave propagation, Photoacoustic imaging, Data acquisition, Radon

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Proceedings Article | 4 March 2008 Paper

Photoacoustic tomography of heterogeneous media using a model-based time reversal method

Hubert Grün, Robert Nuster, Günther Paltauf, Markus Haltmeier, Peter Burgholzer

Proceedings Volume 6856, 685620 (2008) https://doi.org/10.1117/12.763111

KEYWORDS: Sensors, Model-based design, Photoacoustic spectroscopy, Acoustics, Bone, Photoacoustic tomography, Wave propagation, Image restoration, Reconstruction algorithms, Head

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Proceedings Article | 28 February 2008 Paper

Optimizing image resolution in three-dimensional photoacoustic tomography with line detectors

G. Paltauf, R. Nuster, K. Passler, Markus Haltmeier, Peter Burgholzer

Proceedings Volume 6856, 685621 (2008) https://doi.org/10.1117/12.763161

KEYWORDS: Sensors, Acoustics, Signal detection, Image resolution, Optical spheres, Temporal resolution, Gaussian beams, 3D image processing, Reconstruction algorithms, Signal attenuation

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Proceedings Article | 31 July 2007 Paper

Two-dimensional image reconstruction for photo-acoustic tomography with line detectors

G. Paltauf, R. Nuster, P. M. Haltmeier, P. Burgholzer

Proceedings Volume 6631, 663104 (2007) https://doi.org/10.1117/12.729467

KEYWORDS: Sensors, Reconstruction algorithms, 3D image processing, Image restoration, Acoustics, 3D image reconstruction, Photoacoustic tomography, Tissue optics, Inverse optics, Interferometers

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Proceedings Article | 17 July 2007 Paper

Photoacoustic tomography using a fiber based Fabry-Perot interferometer as an integrating line detector and image reconstruction by model-based time reversal method

H. Grün, G. Paltauf, M. Haltmeier, P. Burgholzer

Proceedings Volume 6631, 663107 (2007) https://doi.org/10.1117/12.729475

KEYWORDS: Sensors, Acoustics, Fabry–Perot interferometry, Interferometers, Signal detection, Fiber Bragg gratings, Photoacoustic spectroscopy, Coating, Bone, Reflectivity

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Photoacoustic imaging is based on the generation of acoustic waves in a semitransparent sample (e.g. soft tissue) after illumination with short pulses of light or radio waves. The goal is to recover the spatial distribution of absorbed energy density inside the sample from acoustic pressure signals measured outside the sample (photoacoustic inverse problem). If the acoustic pressure outside the illuminated sample is measured with a large-aperture detector, the signal at a certain time is given by an integral of the generated acoustic pressure distribution over an area that is determined by the shape of the detector. For example a planar detector measures the projections of the initial pressure distribution over planes parallel to the detector plane, which is the Radon transform of the initial pressure distribution. Stable and exact three-dimensional imaging with planar integrating detector requires measurements in all directions of space and so the receiver plane has to be rotated to cover the entire detection surface. We have recently presented a simpler set-up for exact imaging which requires only a single rotation axis and therefor the fragmentation of the area detector into line detectors perpendicular to the rotation axis. Using a two-dimensional reconstruction method and applying the inverse two-dimensional Radon transform afterwards gives an exact reconstruction of the three-dimensional sample with this set-up. In order to achieve high resolution, a fiber based Fabry-Perot interferometer is used. It is a single mode fiber with two fiber bragg gratings on both ends of the line detector. Thermal shifts and vibrations are compensated by frequency locking of the laser. The high resolution and the good performance of this integrating line detector has been demonstrated by photoacoustic measurements with line grid samples and phantoms using a model-based time reversal method for image reconstruction. The time reversed pressure field can be calculated directly by retransmitting the measured pressure on the detector positions in a reversed temporal order.

Proceedings Article | 13 February 2007 Paper

Compensation of acoustic attenuation for high-resolution photoacoustic imaging with line detectors

Peter Burgholzer, Hubert Grün, Markus Haltmeier, Robert Nuster, Günther Paltauf

Proceedings Volume 6437, 643724 (2007) https://doi.org/10.1117/12.700723

KEYWORDS: Sensors, Acoustics, Signal attenuation, Signal detection, Absorption, Photoacoustic imaging, Photoacoustic spectroscopy, Reconstruction algorithms, Radon transform, 3D image processing

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Proceedings Article | 13 February 2007 Paper

Three-dimensional photoacoustic tomography using acoustic line detectors

G. Paltauf, R. Nuster, P. Burgholzer, M. Haltmeier

Proceedings Volume 6437, 64370N (2007) https://doi.org/10.1117/12.700318

KEYWORDS: Sensors, Signal detection, Reconstruction algorithms, Optical spheres, Fourier transforms, Acoustics, Acquisition tracking and pointing, 3D image processing, Image restoration, Detection and tracking algorithms

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Proceedings Article | 6 March 2006 Paper

Thermoacoustic tomography using a fiber-based Fabry-Perot interferometer as an integrating line detector

P. Burgholzer, C. Hofer, G. Matt, G. Paltauf, M. Haltmeier, O. Scherzer

Proceedings Volume 6086, 60861N (2006) https://doi.org/10.1117/12.644047

KEYWORDS: Sensors, Acoustics, Interferometers, Signal detection, Tomography, Radon, Fabry–Perot interferometry, 3D image reconstruction, 3D metrology, Optical spheres

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Proceedings Article | 1 September 2005 Paper

Thermoacoustic tomography using integrating detectors

P. Burgholzer, C. Hofer, G. Paltauf, M. Haltmeier, O. Scherzer

Proceedings Volume 5864, 586403 (2005) https://doi.org/10.1117/12.632908

KEYWORDS: Sensors, Signal detection, Acoustics, Optical spheres, Tomography, Radon transform, Spatial resolution, Ultrasonography, Image resolution, Reconstruction algorithms

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Proceedings Article | 1 September 2005 Paper

Thermoacoustic tomography using optical line detection

G. Paltauf, P. Burgholzer, M. Haltmeier, O. Scherzer

Proceedings Volume 5864, 586402 (2005) https://doi.org/10.1117/12.632907

KEYWORDS: Sensors, Acoustics, Near field optics, 3D image reconstruction, Thermography, Signal detection, 3D image processing, Spatial resolution, Radon transform, Tomography

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Showing 5 of 29 publications

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