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Conductivity
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bioacoustics; iterative image reconstruction
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acoustic tomography
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Approximation methods
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1610
Computed tomography
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1612
Acoustics
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1612
Biology
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DOI Link
1612
Fibers, polarization-maintaining
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1701
Detectors
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Brunker, J.,
Joseph, J.,
Tomaszewski, M.R.,
Morscher, S.,
Bohndiek, S.E.,
Towards Quantitative Evaluation of Tissue Absorption Coefficients
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1701
Absorption
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A Multi-Grid Iterative Method for Photoacoustic Tomography,
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1703
Absorption
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1704
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Deán-Ben, X.L.,
Burton, N.C.,
Sobol, R.W.,
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Constrained Inversion and Spectral Unmixing in Multispectral
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MedImg(36), No. 8, August 2017, pp. 1676-1685.
IEEE DOI
1708
Absorption, Biomedical optical imaging, Image reconstruction,
Optical imaging, Optical scattering, Tomography,
Optoacoustic/photoacoustic tomography, multispectral imaging,
non-negative constraint, spectral, unmixing
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Haltmeier, M.[Markus],
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1708
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Combined Pulse-Echo Ultrasound and Multispectral Optoacoustic
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1710
Anatomical structure, photoacoustic imaging,
ultrasonic transducers, ultrasonography
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Lucka, F.,
Betcke, M.,
Huynh, N.,
Adler, J.,
Cox, B.,
Beard, P.,
Ourselin, S.,
Arridge, S.R.,
Model-Based Learning for Accelerated, Limited-View 3-D Photoacoustic
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MedImg(37), No. 6, June 2018, pp. 1382-1393.
IEEE DOI
1806
Computational modeling, Image reconstruction, Machine learning,
Propagation, TV, Tomography,
photoacoustic tomography
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Florea, M.I.,
Basarab, A.,
Kouamé, D.,
Vorobyov, S.A.,
An Axially Variant Kernel Imaging Model Applied to Ultrasound Image
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SPLetters(25), No. 7, July 2018, pp. 961-965.
IEEE DOI
1807
biomedical ultrasonics, convolution, deconvolution,
image reconstruction, medical image processing,
ultrasound
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Roy, S.,
Borzě, A.,
A New Optimization Approach to Sparse Reconstruction of
Log-Conductivity in Acousto-Electric Tomography,
SIIMS(11), No. 2, 2018, pp. 1759-1784.
DOI Link
1807
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Gupta, M.[Madhu],
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Sparse Reconstruction of Log-Conductivity in Current Density Impedance
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JMIV(62), No. 2, February 2020, pp. 189-205.
Springer DOI
2002
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Yang, H.,
Ntziachristos, V.,
A Bayesian Approach to Eigenspectra Optoacoustic Tomography,
MedImg(37), No. 9, September 2018, pp. 2070-2079.
IEEE DOI
1809
Optical imaging, Inverse problems, Bayes methods,
Biomedical optical imaging, Optical reflection,
spectral unmixing
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Morgan, M.R.,
Broder, J.S.,
Dahl, J.J.,
Herickhoff, C.D.,
Versatile Low-Cost Volumetric 3-D Ultrasound Platform for Existing
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MedImg(37), No. 10, October 2018, pp. 2248-2256.
IEEE DOI
1810
Ultrasonic imaging, Probes,
Sensors, Imaging, Image reconstruction,
system design
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Hossain, M.M.,
Levy, B.E.,
Thapa, D.,
Oldenburg, A.L.,
Gallippi, C.M.,
Blind Source Separation-Based Motion Detector for Imaging
Super-Paramagnetic Iron Oxide (SPIO) Particles in Magnetomotive
Ultrasound Imaging,
MedImg(37), No. 10, October 2018, pp. 2356-2366.
IEEE DOI
1810
Magnetic resonance imaging, Phantoms, Ultrasonic imaging,
Magnetic separation, Blind source separation,
nanoparticles
BibRef
Tang, S.,
Sabonghy, E.P.,
Chaudhry, A.,
Shajudeen, P.S.,
Islam, M.T.,
Kim, N.,
Cabrera, F.J.,
Reddy, J.N.,
Tasciotti, E.,
Righetti, R.,
A Model-Based Approach to Investigate the Effect of a Long Bone
Fracture on Ultrasound Strain Elastography,
MedImg(37), No. 12, December 2018, pp. 2704-2717.
IEEE DOI
1812
Bones, Strain, Solid modeling, Elastography, Biological tissues,
Computed tomography, Ultrasonic imaging, Ultrasound, elastography,
shear strain
BibRef
Nguyen, T.N.,
Do, M.N.,
Oelze, M.L.,
Visualization of the Intensity Field of a Focused Ultrasound Source In
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MedImg(38), No. 1, January 2019, pp. 124-133.
IEEE DOI
1901
Acoustic beams, Visualization, Image reconstruction,
Medical treatment, Imaging, Ultrasonic imaging, Transducers,
bistatic
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Frederick, C.,
Ren, K.,
Vallélian, S.,
Image Reconstruction in Quantitative Photoacoustic Tomography with
the Simplified P_2 Approximation,
SIIMS(11), No. 4, 2018, pp. 2847-2876.
DOI Link
1901
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Lucka, F.,
Huynh, N.,
Betcke, M.,
Zhang, E.,
Beard, P.,
Cox, B.,
Arridge, S.R.,
Enhancing Compressed Sensing 4D Photoacoustic Tomography by
Simultaneous Motion Estimation,
SIIMS(11), No. 4, 2018, pp. 2224-2253.
DOI Link
1901
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Naser, M.A.,
Sampaio, D.R.T.,
Muńoz, N.M.,
Wood, C.A.,
Mitcham, T.M.,
Stefan, W.,
Sokolov, K.V.,
Pavan, T.Z.,
Avritscher, R.,
Bouchard, R.R.,
Improved Photoacoustic-Based Oxygen Saturation Estimation With
SNR-Regularized Local Fluence Correction,
MedImg(38), No. 2, February 2019, pp. 561-571.
IEEE DOI
1902
Signal to noise ratio, Mathematical model, Optical imaging,
Estimation, Finite element analysis, Cancer, Photoacoustic imaging,
image reconstruction methods
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Prakash, J.,
Sanny, D.,
Kalva, S.K.,
Pramanik, M.,
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Fractional Regularization to Improve Photoacoustic Tomographic Image
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MedImg(38), No. 8, August 2019, pp. 1935-1947.
IEEE DOI
1908
Image reconstruction, Imaging, Acoustics, Standards, TV,
Biological tissues, Detectors, Photoacoustic tomography, compressive sensing.
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Haltmeier, M.[Markus],
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Reconstruction Algorithms for Photoacoustic Tomography in Heterogeneous
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Zhao, H.,
Chen, N.,
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Zhang, J.,
Lin, R.,
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Song, L.,
Liu, Z.,
Liu, C.,
Motion Correction in Optical Resolution Photoacoustic Microscopy,
MedImg(38), No. 9, September 2019, pp. 2139-2150.
IEEE DOI
1909
Imaging, Iris, Image segmentation, Mice,
Motion artifacts, Motion segmentation, High resolution imaging,
stitching
BibRef
Drozdov, G.,
Levi, A.,
Rosenthal, A.,
The Impulse Response of Negatively Focused Spherical Ultrasound
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MedImg(38), No. 10, October 2019, pp. 2326-2337.
IEEE DOI
1910
Detectors, Acoustics, Image reconstruction, Noise measurement,
Tomography, Acoustic measurements,
spherical acoustic detectors
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Rathi, N.[Nikita],
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Liu, S.,
Zheng, Y.,
Fast and High-Resolution Three-Dimensional Hybrid-Domain
Photoacoustic Imaging Incorporating Analytical-Focused Transducer
Beam Amplitude,
MedImg(38), No. 12, December 2019, pp. 2926-2936.
IEEE DOI
1912
Transducers, Image reconstruction, Mathematical model, Acoustics,
Imaging, Detectors, Image resolution,
inverse problem
BibRef
Acosta, S.[Sebastian],
Well-Posedness for Photoacoustic Tomography with Fabry-Perot Sensors,
SIIMS(12), No. 4, 2019, pp. 1669-1685.
DOI Link
1912
BibRef
Boink, Y.E.,
Manohar, S.,
Brune, C.,
A Partially-Learned Algorithm for Joint Photo-acoustic Reconstruction
and Segmentation,
MedImg(39), No. 1, January 2020, pp. 129-139.
IEEE DOI
2001
Image reconstruction, Image segmentation, Acoustics, Tomography,
Iterative methods, Acoustic measurements, Inverse problems,
learned iterative reconstruction
BibRef
Li, M.,
Lan, B.,
Sankin, G.,
Zhou, Y.,
Liu, W.,
Xia, J.,
Wang, D.,
Trahey, G.,
Zhong, P.,
Yao, J.,
Simultaneous Photoacoustic Imaging and Cavitation Mapping in
Shockwave Lithotripsy,
MedImg(39), No. 2, February 2020, pp. 468-477.
IEEE DOI
2002
Phase change materials, Injuries, Ultrasonic imaging,
Image reconstruction, Hemorrhaging, Photoacoustic imaging,
cavitation detection
BibRef
Baik, J.W.,
Kim, J.Y.,
Cho, S.,
Choi, S.,
Kim, J.,
Kim, C.,
Super Wide-Field Photoacoustic Microscopy of Animals and Humans In
Vivo,
MedImg(39), No. 4, April 2020, pp. 975-984.
IEEE DOI
2004
Micromechanical devices, Mice, Acoustics, Optical imaging,
Image resolution, Animal imaging, high-speed imaging,
wide-field scanning
BibRef
Jin, H.,
Zhang, R.,
Liu, S.,
Zheng, Y.,
Rapid Three-Dimensional Photoacoustic Imaging Reconstruction for
Irregularly Layered Heterogeneous Media,
MedImg(39), No. 4, April 2020, pp. 1041-1050.
IEEE DOI
2004
Image reconstruction, Media, Acoustics, Transducers,
Mathematical model, Propagation, Imaging,
inverse problem
BibRef
Yang, F.,
Chen, Z.,
Xing, D.,
Single-Cell Photoacoustic Microrheology,
MedImg(39), No. 6, June 2020, pp. 1791-1800.
IEEE DOI
2006
Viscosity, Elasticity, Strain, Laser beams, Cells (biology), Imaging,
Biomedical measurement, Photoacoustic, viscoelasticity imaging,
biomechanical model
BibRef
Ma, X.,
Peng, C.,
Yuan, J.,
Cheng, Q.,
Xu, G.,
Wang, X.,
Carson, P.L.,
Multiple Delay and Sum With Enveloping Beamforming Algorithm for
Photoacoustic Imaging,
MedImg(39), No. 6, June 2020, pp. 1812-1821.
IEEE DOI
2006
Image reconstruction, photoacoustic imaging, optimization, beamforming
BibRef
Sahlström, T.,
Pulkkinen, A.,
Tick, J.,
Leskinen, J.,
Tarvainen, T.,
Modeling of Errors Due to Uncertainties in Ultrasound Sensor
Locations in Photoacoustic Tomography,
MedImg(39), No. 6, June 2020, pp. 2140-2150.
IEEE DOI
2006
Photoacoustic tomography (PAT), inverse problems,
Bayesian methods, error modeling
BibRef
Mahurkar, A.G.,
Seelamantula, C.S.,
Minkowski-Algebra-Based Super-Sparse Array Design for
Super-Resolution Ultrasound Imaging,
SPLetters(27), 2020, pp. 1060-1064.
IEEE DOI
2007
Apertures, Array signal processing, Imaging, Image resolution,
Signal resolution, Ultrasonic imaging, Arrays, Sparse arrays,
ultrasound imaging
BibRef
Chen, J.,
Chen, J.,
Zhuang, R.,
Min, H.,
Multi-Operator Minimum Variance Adaptive Beamforming Algorithms
Accelerated With GPU,
MedImg(39), No. 9, September 2020, pp. 2941-2953.
IEEE DOI
2009
Array signal processing, Optimization, Imaging, Ultrasonic imaging,
Acceleration, Image quality, Graphics processing units,
multi-operator optimization
BibRef
Leino, A.A.,
Lunttila, T.,
Mozumder, M.,
Pulkkinen, A.,
Tarvainen, T.,
Perturbation Monte Carlo Method for Quantitative Photoacoustic
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MedImg(39), No. 10, October 2020, pp. 2985-2995.
IEEE DOI
2010
Optical imaging, Optical scattering, Inverse problems,
Biomedical optical imaging, Monte Carlo methods, Absorption,
image reconstruction
BibRef
Hu, P.,
Li, L.,
Lin, L.,
Wang, L.V.,
Spatiotemporal Antialiasing in Photoacoustic Computed Tomography,
MedImg(39), No. 11, November 2020, pp. 3535-3547.
IEEE DOI
2011
Image reconstruction, Ultrasonic transducers,
Spatiotemporal phenomena, Cutoff frequency, temporal filtering
BibRef
Li, X.,
Zhang, S.,
Wu, J.,
Huang, S.,
Feng, Q.,
Qi, L.,
Chen, W.,
Multispectral Interlaced Sparse Sampling Photoacoustic Tomography,
MedImg(39), No. 11, November 2020, pp. 3463-3474.
IEEE DOI
2011
Transducers, Image reconstruction, Detectors, Tomography, Absorption,
Switches, Sparse sampling,
spectral un-mixing
BibRef
Kim, M.,
Jeng, G.S.,
Pelivanov, I.,
O'Donnell, M.,
Deep-Learning Image Reconstruction for Real-Time Photoacoustic System,
MedImg(39), No. 11, November 2020, pp. 3379-3390.
IEEE DOI
2011
Image reconstruction, Imaging, Bandwidth, Geometry,
Real-time systems, Standards, Delays, Photoacoustic imaging,
convolutional neural network
BibRef
Zhang, Y.,
Wang, L.,
Video-Rate Ring-Array Ultrasound and Photoacoustic Tomography,
MedImg(39), No. 12, December 2020, pp. 4369-4375.
IEEE DOI
2012
Image reconstruction, Data acquisition, Tomography, Acoustics,
Ultrasonic imaging, Image resolution, Photoacoustic tomography,
plane wave
BibRef
Aspri, A.[Andrea],
Beretta, E.[Elena],
Scherzer, O.[Otmar],
Muszkieta, M.[Monika],
Asymptotic Expansions for Higher Order Elliptic Equations with an
Application to Quantitative Photoacoustic Tomography,
SIIMS(13), No. 4, 2020, pp. 1781-1833.
DOI Link
2012
BibRef
Li, M.,
Vu, T.,
Sankin, G.,
Winship, B.,
Boydston, K.,
Terry, R.,
Zhong, P.,
Yao, J.,
Internal-Illumination Photoacoustic Tomography Enhanced by a
Graded-Scattering Fiber Diffuser,
MedImg(40), No. 1, January 2021, pp. 346-356.
IEEE DOI
2012
Optical fibers, Optical scattering, Optical imaging, Lighting,
Biomedical optical imaging, Deep imaging, graded scattering,
swine model
BibRef
DiSpirito, A.,
Li, D.,
Vu, T.,
Chen, M.,
Zhang, D.,
Luo, J.,
Horstmeyer, R.,
Yao, J.,
Reconstructing Undersampled Photoacoustic Microscopy Images Using
Deep Learning,
MedImg(40), No. 2, February 2021, pp. 562-570.
IEEE DOI
2102
Deep learning, Image reconstruction, Biomedical optical imaging,
High-speed optical techniques, Optical imaging, undersampled images
BibRef
Zhao, X.B.[Xue-Bin],
Zhou, H.[Hui],
Chen, H.M.[Han-Ming],
Wang, Y.F.[Yu-Feng],
Domain Decomposition for Large-Scale Viscoacoustic Wave Simulation
Using Localized Pseudo-Spectral Method,
GeoRS(59), No. 3, March 2021, pp. 2666-2679.
IEEE DOI
2103
Mathematical model, Laplace equations, Absorption, Media,
Attenuation, Computational modeling, Domain decomposition,
pseudo-spectral method
BibRef
Lunz, S.[Sebastian],
Hauptmann, A.[Andreas],
Tarvainen, T.[Tanja],
Schönlieb, C.B.[Carola-Bibiane],
Arridge, S.[Simon],
On Learned Operator Correction in Inverse Problems,
SIIMS(14), No. 1, 2021, pp. 92-127.
DOI Link
2104
BibRef
Xiao, D.[Di],
Yiu, B.Y.S.[Billy Y. S.],
Chee, A.J.Y.[Adrian J. Y.],
Yu, A.C.H.[Alfred C. H.],
Channel Count Reduction for Plane Wave Ultrasound Through Convolutional
Neural Network Interpolation,
ICIAR19(II:442-451).
Springer DOI
1909
BibRef
Ben Daya, I.[Ibrahim],
Yeow, J.T.W.[John T. W.],
Wong, A.[Alexander],
Compensated Row-Column Ultrasound Imaging Systems with Data-Driven
Point Spread Function Learning,
ICIAR19(II:429-441).
Springer DOI
1909
BibRef
Tagawa, N.,
Zhu, J.,
Super-Resolution Ultrasound Imaging Based on the Phase of the Carrier
Wave Without Deterioration by Grating Lobes,
ICPR18(2791-2796)
IEEE DOI
1812
Image resolution, Imaging, Transducers, Gratings, Signal resolution,
Ultrasonic imaging, Frequency modulation
BibRef
Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Freehand Ultrasound, Ultrasonic, Generation .