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Mark A. Anastasio
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2020 – today
- 2024
- [j41]Ruiyang Zhao
, Xi Peng
, Varun A. Kelkar, Mark A. Anastasio
, Fan Lam
:
High-Dimensional MR Reconstruction Integrating Subspace and Adaptive Generative Models. IEEE Trans. Biomed. Eng. 71(6): 1969-1979 (2024) - [j40]Luke Lozenski
, Hanchen Wang
, Fu Li
, Mark A. Anastasio
, Brendt Wohlberg
, Youzuo Lin
, Umberto Villa
:
Learned Full Waveform Inversion Incorporating Task Information for Ultrasound Computed Tomography. IEEE Trans. Computational Imaging 10: 69-82 (2024) - [j39]Sourya Sengupta
, Mark A. Anastasio
:
A Test Statistic Estimation-Based Approach for Establishing Self-Interpretable CNN-Based Binary Classifiers. IEEE Trans. Medical Imaging 43(5): 1753-1765 (2024) - [j38]Varun A. Kelkar, Rucha Deshpande, Arindam Banerjee, Mark A. Anastasio:
AmbientFlow: Invertible generative models from incomplete, noisy measurements. Trans. Mach. Learn. Res. 2024 (2024) - [i34]Rucha Deshpande, Varun A. Kelkar, Dimitrios S. Gotsis, Prabhat K. C., Rongping Zeng, Kyle J. Myers, Frank J. Brooks, Mark A. Anastasio:
Report on the AAPM Grand Challenge on deep generative modeling for learning medical image statistics. CoRR abs/2405.01822 (2024) - [i33]Zhuchen Shao, Mark A. Anastasio, Hua Li:
Prior-guided Diffusion Model for Cell Segmentation in Quantitative Phase Imaging. CoRR abs/2405.06175 (2024) - 2023
- [j37]Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Prabhat K. C.
, Kyle J. Myers
, Rongping Zeng
, Mark A. Anastasio
:
Assessing the Ability of Generative Adversarial Networks to Learn Canonical Medical Image Statistics. IEEE Trans. Medical Imaging 42(6): 1799-1808 (2023) - [j36]Weimin Zhou
, Umberto Villa
, Mark A. Anastasio
:
Ideal Observer Computation by Use of Markov-Chain Monte Carlo With Generative Adversarial Networks. IEEE Trans. Medical Imaging 42(12): 3715-3724 (2023) - [c38]Kaiyan Li, Weimin Zhou, Hua Li, Mark A. Anastasio:
Estimating task-based performance bounds for image reconstruction methods by use of learned-ideal observers. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2023 - [c37]Varun A. Kelkar, Dimitrios S. Gotsis, Rucha Deshpande, Frank J. Brooks, Prabhat K. C., Kyle J. Myers, Rongping Zeng, Mark A. Anastasio:
Evaluating generative stochastic image models using task-based image quality measures. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2023 - [i32]Sourya Sengupta, Mark A. Anastasio:
Revisiting model self-interpretability in a decision-theoretic way for binary medical image classification. CoRR abs/2303.06876 (2023) - [i31]Weimin Zhou, Umberto Villa, Mark A. Anastasio:
Ideal Observer Computation by Use of Markov-Chain Monte Carlo with Generative Adversarial Networks. CoRR abs/2304.00433 (2023) - [i30]Ruiyang Zhao, Xi Peng, Varun A. Kelkar, Mark A. Anastasio, Fan Lam:
High-Dimensional MR Reconstruction Integrating Subspace and Adaptive Generative Models. CoRR abs/2306.08630 (2023) - [i29]Varun A. Kelkar, Rucha Deshpande, Arindam Banerjee, Mark A. Anastasio:
AmbientFlow: Invertible generative models from incomplete, noisy measurements. CoRR abs/2309.04856 (2023) - [i28]Rucha Deshpande, Muzaffer Özbey, Hua Li, Mark A. Anastasio, Frank J. Brooks:
Assessing the capacity of a denoising diffusion probabilistic model to reproduce spatial context. CoRR abs/2309.10817 (2023) - 2022
- [j35]Luke Lozenski
, Mark A. Anastasio
, Umberto Villa
:
A Memory-Efficient Self-Supervised Dynamic Image Reconstruction Method Using Neural Fields. IEEE Trans. Computational Imaging 8: 879-892 (2022) - [j34]Kaiyan Li
, Weimin Zhou
, Hua Li
, Mark A. Anastasio
:
A Hybrid Approach for Approximating the Ideal Observer for Joint Signal Detection and Estimation Tasks by Use of Supervised Learning and Markov-Chain Monte Carlo Methods. IEEE Trans. Medical Imaging 41(5): 1114-1124 (2022) - [c36]Rucha Deshpande, Mark A. Anastasio, Frank J. Brooks:
Evaluating the capacity of deep generative models to reproduce measurable high-order spatial arrangements in diagnostic images. Medical Imaging: Image Processing 2022 - [c35]Zong Fan, Varun A. Kelkar, Mark A. Anastasio, Hua Li:
Application of DatasetGAN in medical imaging: preliminary studies. Medical Imaging: Image Processing 2022 - [c34]Kaiyan Li, Hua Li, Mark A. Anastasio:
A task-informed model training method for deep neural network-based image denoising. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2022 - [c33]Craig K. Abbey, Sourya Sengupta, Weimin Zhou, Andreu Badal, Rongping Zeng, Frank W. Samuelson, Miguel P. Eckstein, Kyle J. Myers, Mark A. Anastasio, Jovan G. Brankov
:
Analyzing neural networks applied to an anatomical simulation of the breast. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2022 - [c32]Jason L. Granstedt, Fu Li
, Umberto Villa, Mark A. Anastasio:
Learned Hotelling observers for use with multi-modal data. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2022 - [c31]Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Kyle J. Myers, Prabhat K. C., Rongping Zeng, Mark A. Anastasio:
Evaluating procedures for establishing generative adversarial network-based stochastic image models in medical imaging. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2022 - [c30]Sourya Sengupta, Craig K. Abbey, Kaiyan Li, Mark A. Anastasio:
Investigation of adversarial robust training for establishing interpretable CNN-based numerical observers. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2022 - [i27]Sayantan Bhadra, Umberto Villa, Mark A. Anastasio:
Mining the manifolds of deep generative models for multiple data-consistent solutions of ill-posed tomographic imaging problems. CoRR abs/2202.05311 (2022) - [i26]Varun A. Kelkar, Mark A. Anastasio:
Prior image-based medical image reconstruction using a style-based generative adversarial network. CoRR abs/2202.08936 (2022) - [i25]Zong Fan, Varun A. Kelkar, Mark A. Anastasio, Hua Li:
Application of DatasetGAN in medical imaging: preliminary studies. CoRR abs/2202.13463 (2022) - [i24]Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Kyle J. Myers, Prabhat K. C., Rongping Zeng, Mark A. Anastasio:
Evaluating Procedures for Establishing Generative Adversarial Network-based Stochastic Image Models in Medical Imaging. CoRR abs/2204.03547 (2022) - [i23]Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Prabhat K. C., Kyle J. Myers, Rongping Zeng, Mark A. Anastasio:
Assessing the ability of generative adversarial networks to learn canonical medical image statistics. CoRR abs/2204.12007 (2022) - [i22]Rucha Deshpande, Ashish Avachat, Frank J. Brooks, Mark A. Anastasio:
Investigating the robustness of a learning-based method for quantitative phase retrieval from propagation-based x-ray phase contrast measurements under laboratory conditions. CoRR abs/2211.01372 (2022) - 2021
- [j33]Shenghua He, Kyaw Thu Minn
, Lilianna Solnica-Krezel
, Mark A. Anastasio, Hua Li:
Deeply-supervised density regression for automatic cell counting in microscopy images. Medical Image Anal. 68: 101892 (2021) - [j32]Kalyan Tripathy, Zachary E. Markow
, Andrew K. Fishell, Arefeh Sherafati, Tracy M. Burns-Yocum, Mariel L. Schroeder, Alexandra M. Svoboda
, Adam T. Eggebrecht, Mark A. Anastasio
, Bradley L. Schlaggar, Joseph P. Culver:
Decoding visual information from high-density diffuse optical tomography neuroimaging data. NeuroImage 226: 117516 (2021) - [j31]Varun A. Kelkar, Sayantan Bhadra, Mark A. Anastasio
:
Compressible Latent-Space Invertible Networks for Generative Model-Constrained Image Reconstruction. IEEE Trans. Computational Imaging 7: 209-223 (2021) - [j30]Kaiyan Li
, Weimin Zhou
, Hua Li
, Mark A. Anastasio
:
Assessing the Impact of Deep Neural Network-Based Image Denoising on Binary Signal Detection Tasks. IEEE Trans. Medical Imaging 40(9): 2295-2305 (2021) - [j29]Sayantan Bhadra
, Varun A. Kelkar, Frank J. Brooks, Mark A. Anastasio
:
On Hallucinations in Tomographic Image Reconstruction. IEEE Trans. Medical Imaging 40(11): 3249-3260 (2021) - [c29]Varun A. Kelkar, Mark A. Anastasio:
Prior Image-Constrained Reconstruction using Style-Based Generative Models. ICML 2021: 5367-5377 - [c28]Jason L. Granstedt, Varun A. Kelkar, Weimin Zhou, Mark A. Anastasio:
SlabGAN: a method for generating efficient 3D anisotropic medical volumes using generative adversarial networks. Medical Imaging: Image Processing 2021 - [c27]Kaiyan Li, Weimin Zhou, Hua Li, Mark A. Anastasio:
Supervised learning-based ideal observer approximation for joint detection and estimation tasks. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2021 - [c26]Kaiyan Li, Weimin Zhou, Hua Li, Mark A. Anastasio:
Task-based performance evaluation of deep neural network-based image denoising. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2021 - [c25]Sayantan Bhadra, Varun A. Kelkar, Frank J. Brooks, Mark A. Anastasio:
Assessing regularization in tomographic imaging via hallucinations in the null space. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2021 - [c24]Varun A. Kelkar, Xiaohui Zhang
, Jason L. Granstedt, Hua Li, Mark A. Anastasio:
Task-based evaluation of deep image super-resolution in medical imaging. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2021 - [c23]John Paul Phillips, Emil Y. Sidky, Greg Ongie, Weimin Zhou, Juan-Pablo Cruz-Bastida
, Ingrid S. Reiser, Mark A. Anastasio, Xiaochuan Pan:
A hybrid channelized Hotelling observer for estimating the ideal linear observer for total-variation-based image reconstruction. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2021 - [c22]Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Jason L. Granstedt, Hua Li, Mark A. Anastasio:
Advancing the AmbientGAN for learning stochastic object models. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2021 - [i21]Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Jason L. Granstedt, Hua Li, Mark A. Anastasio:
Advancing the AmbientGAN for learning stochastic object models. CoRR abs/2102.00281 (2021) - [i20]Varun A. Kelkar, Mark A. Anastasio:
Prior Image-Constrained Reconstruction using Style-Based Generative Models. CoRR abs/2102.12525 (2021) - [i19]Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio:
Learning stochastic object models from medical imaging measurements by use of advanced AmbientGANs. CoRR abs/2106.14324 (2021) - [i18]Xiaohui Zhang, Varun A. Kelkar, Jason L. Granstedt, Hua Li, Mark A. Anastasio:
Impact of deep learning-based image super-resolution on binary signal detection. CoRR abs/2107.02338 (2021) - [i17]Rucha Deshpande, Mark A. Anastasio, Frank J. Brooks:
A Method for Evaluating the Capacity of Generative Adversarial Networks to Reproduce High-order Spatial Context. CoRR abs/2111.12577 (2021) - 2020
- [j28]Weimin Zhou
, Hua Li, Mark A. Anastasio
:
Approximating the Ideal Observer for Joint Signal Detection and Localization Tasks by use of Supervised Learning Methods. IEEE Trans. Medical Imaging 39(12): 3992-4000 (2020) - [c21]Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio:
Learning efficient channels with a dual loss autoencoder. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160C - [c20]Shenghua He, Weimin Zhou, Hua Li, Mark A. Anastasio:
Learning numerical observers using unsupervised domain adaptation. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160W - [c19]Weimin Zhou, Mark A. Anastasio:
Markov-Chain Monte Carlo approximation of the Ideal Observer using generative adversarial networks. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160D - [c18]Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio:
Progressively-Growing AmbientGANs for learning stochastic object models from imaging measurements. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2020: 113160Q - [i16]Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio:
Progressively-Growing AmbientGANs For Learning Stochastic Object Models From Imaging Measurements. CoRR abs/2001.09523 (2020) - [i15]Weimin Zhou, Mark A. Anastasio:
Markov-Chain Monte Carlo Approximation of the Ideal Observer using Generative Adversarial Networks. CoRR abs/2001.09526 (2020) - [i14]Sayantan Bhadra, Weimin Zhou, Mark A. Anastasio:
Medical image reconstruction with image-adaptive priors learned by use of generative adversarial networks. CoRR abs/2001.10830 (2020) - [i13]Shenghua He, Weimin Zhou, Hua Li, Mark A. Anastasio:
Learning Numerical Observers using Unsupervised Domain Adaptation. CoRR abs/2002.03763 (2020) - [i12]Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio:
Approximating the Hotelling Observer with Autoencoder-Learned Efficient Channels for Binary Signal Detection Tasks. CoRR abs/2003.02321 (2020) - [i11]Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio:
Learning stochastic object models from medical imaging measurements using Progressively-Growing AmbientGANs. CoRR abs/2006.00033 (2020) - [i10]Weimin Zhou, Hua Li, Mark A. Anastasio:
Approximating the Ideal Observer for joint signal detection and localization tasks by use of supervised learning methods. CoRR abs/2006.00112 (2020) - [i9]Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Mark A. Anastasio, Hua Li:
Deeply-Supervised Density Regression for Automatic Cell Counting in Microscopy Images. CoRR abs/2011.03683 (2020) - [i8]Sayantan Bhadra, Varun A. Kelkar, Frank J. Brooks, Mark A. Anastasio:
On hallucinations in tomographic image reconstruction. CoRR abs/2012.00646 (2020)
2010 – 2019
- 2019
- [j27]Yang Lou, Seonyeong Park
, Fatima Anis, Richard Su, Alexander A. Oraevsky, Mark A. Anastasio
:
Analysis of the Use of Unmatched Backward Operators in Iterative Image Reconstruction With Application to Three-Dimensional Optoacoustic Tomography. IEEE Trans. Computational Imaging 5(3): 437-449 (2019) - [j26]Yujia Chen
, Yang Lou, Kun Wang
, Matthew A. Kupinski, Mark A. Anastasio
:
Reconstruction-Aware Imaging System Ranking by Use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference. IEEE Trans. Medical Imaging 38(5): 1251-1262 (2019) - [j25]Weimin Zhou
, Hua Li, Mark A. Anastasio
:
Approximating the Ideal Observer and Hotelling Observer for Binary Signal Detection Tasks by Use of Supervised Learning Methods. IEEE Trans. Medical Imaging 38(10): 2456-2468 (2019) - [c17]Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Mark A. Anastasio, Hua Li:
Automatic microscopic cell counting by use of deeply-supervised density regression model. Medical Imaging: Digital Pathology 2019: 109560L - [c16]Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Hua Li, Mark A. Anastasio:
Automatic microscopic cell counting by use of unsupervised adversarial domain adaptation and supervised density regression. Medical Imaging: Digital Pathology 2019: 1095604 - [c15]Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Mark A. Anastasio:
Learning stochastic object model from noisy imaging measurements using AmbientGANs. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2019: 109520M - [c14]Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio:
Autoencoder embedding of task-specific information. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2019: 1095207 - [c13]Weimin Zhou, Hua Li, Mark A. Anastasio:
Learning the Hotelling observer for SKE detection tasks by use of supervised learning methods. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2019: 1095208 - [c12]Weimin Zhou, Mark A. Anastasio:
Learning the ideal observer for joint detection and localization tasks by use of convolutional neural networks. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2019: 1095209 - [i7]Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Hua Li, Mark A. Anastasio:
Automatic microscopic cell counting by use of unsupervised adversarial domain adaptation and supervised density regression. CoRR abs/1903.00388 (2019) - [i6]Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Mark A. Anastasio, Hua Li:
Automatic microscopic cell counting by use of deeply-supervised density regression model. CoRR abs/1903.01084 (2019) - [i5]Joemini Poudel, Yang Lou, Mark A. Anastasio:
A survey of computational frameworks for solving the acoustic inverse problem in three-dimensional photoacoustic computed tomography. CoRR abs/1905.03881 (2019) - [i4]Yujia Chen, Yang Lou, Kun Wang, Matthew A. Kupinski, Mark A. Anastasio:
Reconstruction-Aware Imaging System Ranking by use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference. CoRR abs/1905.05820 (2019) - [i3]Weimin Zhou, Hua Li, Mark A. Anastasio:
Approximating the Ideal Observer and Hotelling Observer for binary signal detection tasks by use of supervised learning methods. CoRR abs/1905.06330 (2019) - 2018
- [j24]Jian Wu, Thomas R. Mazur, Su Ruan
, Chunfeng Lian, Nalini Daniel, Hilary Lashmett, Laura Ochoa, Imran Zoberi, Mark A. Anastasio, H. Michael Gach, Sasa Mutic, Maria Thomas, Hua Li:
A deep Boltzmann machine-driven level set method for heart motion tracking using cine MRI images. Medical Image Anal. 47: 68-80 (2018) - [j23]Thomas P. Matthews, Joemini Poudel, Lei Li, Lihong V. Wang, Mark A. Anastasio
:
Parameterized Joint Reconstruction of the Initial Pressure and Sound Speed Distributions for Photoacoustic Computed Tomography. SIAM J. Imaging Sci. 11(2): 1560-1588 (2018) - [c11]Jian Wu, Su Ruan
, Chunfeng Lian, Sasa Mutic, Mark A. Anastasio, Hua Li:
Active learning with noise modeling for medical image annotation. ISBI 2018: 298-301 - [c10]Jian Wu, Su Ruan
, Thomas R. Mazur, Nalini Daniel, Hilary Lashmett, Laura Ochoa, Imran Zoberi, Chunfeng Lian, H. Michael Gach, Sasa Mutic, Maria Thomas, Mark A. Anastasio, Hua Li:
Heart motion tracking on cine MRI based on a deep Boltzmann machine-driven level set method. ISBI 2018: 1153-1156 - [c9]Shenghua He, Jie Zheng, Akiko Maehara, Gary S. Mintz, Dalin Tang, Mark A. Anastasio, Hua Li:
Convolutional neural network based automatic plaque characterization for intracoronary optical coherence tomography images. Medical Imaging: Image Processing 2018: 1057432 - [c8]Weimin Zhou, Mark A. Anastasio:
Learning the ideal observer for SKE detection tasks by use of convolutional neural networks. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2018: 1057719 - [i2]Shenghua He, Jie Zheng, Akiko Maehara, Gary S. Mintz, Dalin Tang, Mark A. Anastasio, Hua Li:
Convolutional neural network based automatic plaque characterization from intracoronary optical coherence tomography images. CoRR abs/1807.03613 (2018) - 2017
- [j22]Kenji Mitsuhashi, Joemini Poudel, Thomas P. Matthews, Alejandro Garcia-Uribe, Lihong V. Wang, Mark A. Anastasio:
A Forward-Adjoint Operator Pair Based on the Elastic Wave Equation for Use in Transcranial Photoacoustic Computed Tomography. SIAM J. Imaging Sci. 10(4): 2022-2048 (2017) - [i1]Brendan Kelly, Thomas P. Matthews, Mark A. Anastasio:
Deep Learning-Guided Image Reconstruction from Incomplete Data. CoRR abs/1709.00584 (2017) - 2016
- [j21]Chao Huang, Kun Wang, Robert W. Schoonover, Lihong V. Wang, Mark A. Anastasio:
Joint Reconstruction of Absorbed Optical Energy Density and Sound Speed Distributions in Photoacoustic Computed Tomography: A Numerical Investigation. IEEE Trans. Computational Imaging 2(2): 136-149 (2016) - 2015
- [r1]Kun Wang, Mark A. Anastasio:
Photoacoustic and Thermoacoustic Tomography: Image Formation Principles. Handbook of Mathematical Methods in Imaging 2015: 1081-1116 - 2014
- [j20]Kun Wang, Robert W. Schoonover, Richard Su, Alexander A. Oraevsky
, Mark A. Anastasio:
Discrete Imaging Models for Three-Dimensional Optoacoustic Tomography Using Radially Symmetric Expansion Functions. IEEE Trans. Medical Imaging 33(5): 1180-1193 (2014) - [j19]Alex Sawatzky, Qiaofeng Xu, Carsten Oliver Schirra, Mark A. Anastasio:
Proximal ADMM for Multi-Channel Image Reconstruction in Spectral X-ray CT. IEEE Trans. Medical Imaging 33(8): 1657-1668 (2014) - 2013
- [j18]Chao Huang, Kun Wang, Liming Nie, Lihong V. Wang
, Mark A. Anastasio:
Full-Wave Iterative Image Reconstruction in Photoacoustic Tomography With Acoustically Inhomogeneous Media. IEEE Trans. Medical Imaging 32(6): 1097-1110 (2013) - [j17]Carsten Oliver Schirra, Ewald Roessl, Thomas Köhler, Bernhard Brendel, Axel Thran, Dipanjan Pan
, Mark A. Anastasio, Roland Proksa:
Statistical Reconstruction of Material Decomposed Data in Spectral CT. IEEE Trans. Medical Imaging 32(7): 1249-1257 (2013) - 2011
- [j16]Kun Wang, Sergey A. Ermilov, Richard Su, Hans-Peter Brecht, Alexander A. Oraevsky
, Mark A. Anastasio:
An Imaging Model Incorporating Ultrasonic Transducer Properties for Three-Dimensional Optoacoustic Tomography. IEEE Trans. Medical Imaging 30(2): 203-214 (2011)
2000 – 2009
- 2009
- [j15]Jin Zhang, Mark A. Anastasio, Patrick J. La Rivière, Lihong V. Wang
:
Effects of Different Imaging Models on Least-Squares Image Reconstruction Accuracy in Photoacoustic Tomography. IEEE Trans. Medical Imaging 28(11): 1781-1790 (2009) - [j14]Daxin Shi, Mark A. Anastasio:
Relationships Between Smooth- and Small-Phase Conditions in X-Ray Phase-Contrast Imaging. IEEE Trans. Medical Imaging 28(12): 1969-1973 (2009) - 2006
- [c7]Miles N. Wernick, Jovan G. Brankov, Dean Chapman, Yongyi Yang, Gocha Khelashvili, Mark A. Anastasio, Zhong Zhong, Christopher Parham, Jun Li, Carol Muehleman:
Progress in multiple-image radiography. Computational Imaging 2006: 60650W - 2005
- [j13]Mark A. Anastasio, Jin Zhang, Xiaochuan Pan, Yu Zou, Geng Ku, Lihong V. Wang
:
Half-time image reconstruction in thermoacoustic tomography. IEEE Trans. Medical Imaging 24(2): 199-210 (2005) - [j12]Jin Zhang, Mark A. Anastasio, Xiaochuan Pan, Lihong V. Wang
:
Weighted expectation maximization reconstruction algorithms for thermoacoustic tomography. IEEE Trans. Medical Imaging 24(6): 817-820 (2005) - [j11]Mark A. Anastasio, Jin Zhang, Emil Y. Sidky, Yu Zou, Dan Xia, Xiaochuan Pan:
Feasibility of half-data image reconstruction in 3-D reflectivity tomography with a spherical aperture. IEEE Trans. Medical Imaging 24(9): 1100-1112 (2005) - 2004
- [c6]Miles N. Wernick, Jovan G. Brankov, Dean Chapman, Mark A. Anastasio, Zhong Zhong, Carol Muehleman, Jun Li:
Multiple-Image Computed Tomography. ISBI 2004: 948-951 - 2003
- [j10]Mark A. Anastasio, Xiaochuan Pan:
An improved reconstruction algorithm for 3-D diffraction tomography using spherical-wave sources. IEEE Trans. Biomed. Eng. 50(4): 517-521 (2003) - [j9]Xiaochuan Pan, Yu Zou, Mark A. Anastasio:
Data redundancy and reduced-scan reconstruction in reflectivity tomography. IEEE Trans. Image Process. 12(7): 784-795 (2003) - [c5]Daxin Shi, Mark A. Anastasio, Xiaochuan Pan, Charles A. Pelizzari, Peter Munro:
Investigation of megavoltage local tomography for detecting setup errors in radiation therapy. Medical Imaging: Image-Guided Procedures 2003 - 2002
- [j8]Mark A. Anastasio, Xiaochuan Pan:
Numerically robust minimal-scan reconstruction algorithms for diffraction tomography via radon transform inversion. Int. J. Imaging Syst. Technol. 12(2): 84-91 (2002) - [j7]Xiaochuan Pan, Mark A. Anastasio:
On a limited-view reconstruction problem in wavefield tomography. IEEE Trans. Medical Imaging 21(4): 413-416 (2002) - [c4]Xiaochuan Pan, Yu Zou, Mark A. Anastasio:
Image reconstruction of reflectivity from short scan data. ISBI 2002: 1027-1030 - 2001
- [j6]Mark A. Anastasio, Xiaochuan Pan, Eric Clarkson:
Comments on the Filtered Backprojection Algorithm, Range Conditions, and the Pseudoinverse Solution. IEEE Trans. Medical Imaging 20(6): 539-542 (2001) - [c3]Mark A. Anastasio, Xiaochuan Pan:
Development and evaluation of minimal-scan reconstruction algorithms for diffraction tomography. Medical Imaging: Image Processing 2001 - 2000
- [j5]Mark A. Anastasio, Xiaochuan Pan:
A new reconstruction approach for reflection mode diffraction tomography. IEEE Trans. Image Process. 9(7): 1262-1271 (2000) - [c2]Matthew A. Kupinski, Mark A. Anastasio, Maryellen Lissak Giger:
Multiobjective genetic optimization of diagnostic classifiers used in the computerized detection of mass lesions in mammography. Medical Imaging: Image Processing 2000
1990 – 1999
- 1999
- [j4]Mark A. Anastasio, Xiaochuan Pan:
Investigation of the noise properties of a new class of reconstruction methods in diffraction tomography. Int. J. Imaging Syst. Technol. 10(6): 437-446 (1999) - [j3]Mark A. Anastasio, Xiaochuan Pan, Chien-Min Kao
:
Multidimensional smoothing using orthogonal expansions. IEEE Signal Process. Lett. 6(4): 91-94 (1999) - [j2]Matthew A. Kupinski, Mark A. Anastasio:
Multiobjective Genetic Optimization of Diagnostic Classifiers with Implications for Generating ROC Curves. IEEE Trans. Medical Imaging 18(8): 675-685 (1999) - 1998
- [j1]Mark A. Anastasio, Matthew A. Kupinski, Robert M. Nishikawa
:
Optimization and FROC Analysis of Rule-Based Detection Schemes Using a Multiobjective Approach. IEEE Trans. Medical Imaging 17(6): 1089-1093 (1998) - [c1]Mark A. Anastasio, Xiaochuan Pan, Chien-Min Kao:
A General Technique for Smoothing Multi-Dimensional Datasets Utilizing Orthogonal Expansions and Lower Dimensional Smoothers. ICIP (2) 1998: 718-721
Coauthor Index
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For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
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Citation data
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load citations from opencitations.net
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last updated on 2024-08-14 23:16 CEST by the dblp team
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