Mark A. Anastasio

127 papers A* 1B 6Journal 87Unranked 32

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Learning-based Framework for Spatial Impulse Response Compensation in 3D Photoacoustic Computed Tomography. CoRR Kaiyi Yang, Seonyeong Park, Gangwon Jeong, Hsuan-Kai Huang, Alexander A. Oraevsky, Umberto Villa, Mark A. Anastasio
2026	J	`jnl`	Benchmarking Deep Learning-Based Reconstruction Methods for Photoacoustic Computed Tomography with Clinically Relevant Synthetic Datasets. CoRR Panpan Chen, Seonyeong Park, Gangwon Jeong, Refik Mert Çam, Umberto Villa, Mark A. Anastasio
2026	J	`jnl`	Learning a Filtered Backprojection Reconstruction Method for Photoacoustic Computed Tomography With Hemispherical Measurement Geometries. IEEE Trans. Medical Imaging Panpan Chen, Seonyeong Park, Refik Mert Çam, Hsuan-Kai Huang, Alexander A. Oraevsky, Umberto Villa, Mark A. Anastasio
2025	J	`jnl`	Application of a Virtual Imaging Framework for Investigating a Deep Learning-Based Reconstruction Method for 3D Quantitative Photoacoustic Computed Tomography. CoRR Refik Mert Çam, Seonyeong Park, Umberto Villa, Mark A. Anastasio
2025	J	`jnl`	Full-Wave Image Reconstruction in Transcranial Photoacoustic Computed Tomography Using a Finite Element Method. IEEE Trans. Medical Imaging Yilin Luo, Hsuan-Kai Huang, Karteekeya Sastry, Peng Hu, Xin Tong, Joseph Kuo, Yousuf Abo Rahama, Shuai Na, Umberto Villa, Mark A. Anastasio, Lihong V. Wang
2024	J	`jnl`	A Test Statistic Estimation-Based Approach for Establishing Self-Interpretable CNN-Based Binary Classifiers. IEEE Trans. Medical Imaging Sourya Sengupta, Mark A. Anastasio
2024	J	`jnl`	A method for evaluating deep generative models of images for hallucinations in high-order spatial context. Pattern Recognit. Lett. Rucha Deshpande, Mark A. Anastasio, Frank J. Brooks
2024	J	`jnl`	AmbientFlow: Invertible generative models from incomplete, noisy measurements. Trans. Mach. Learn. Res. Varun A. Kelkar, Rucha Deshpande, Arindam Banerjee, Mark A. Anastasio
2024	J	`jnl`	Assessing the Capacity of a Denoising Diffusion Probabilistic Model to Reproduce Spatial Context. IEEE Trans. Medical Imaging Rucha Deshpande, Muzaffer Özbey, Hua Li, Mark A. Anastasio, Frank J. Brooks
2024	J	`jnl`	High-Dimensional MR Reconstruction Integrating Subspace and Adaptive Generative Models. IEEE Trans. Biomed. Eng. Ruiyang Zhao, Xi Peng, Varun A. Kelkar, Mark A. Anastasio, Fan Lam
2024	J	`jnl`	Learned Full Waveform Inversion Incorporating Task Information for Ultrasound Computed Tomography. IEEE Trans. Computational Imaging Luke Lozenski, Hanchen Wang, Fu Li, Mark A. Anastasio, Brendt Wohlberg, Youzuo Lin, Umberto Villa
2024	J	`jnl`	Learning a Filtered Backprojection Reconstruction Method for Photoacoustic Computed Tomography with Hemispherical Measurement Geometries. CoRR Panpan Chen, Seonyeong Park, Refik Mert Çam, Hsuan-Kai Huang, Alexander A. Oraevsky, Umberto Villa, Mark A. Anastasio
2024	J	`jnl`	Optimizing Quantitative Photoacoustic Imaging Systems: The Bayesian Cramér-Rao Bound Approach. CoRR Evan Scope Crafts, Mark A. Anastasio, Umberto Villa
2024	J	`jnl`	Physics and Deep Learning in Computational Wave Imaging. CoRR Youzuo Lin, Shihang Feng, James Theiler, Yinpeng Chen, Umberto Villa, Jing Rao, John James Greenhall, Cristian Pantea, Mark A. Anastasio, Brendt Wohlberg
2024	J	`jnl`	Prior-guided Diffusion Model for Cell Segmentation in Quantitative Phase Imaging. CoRR Zhuchen Shao, Mark A. Anastasio, Hua Li
2024	J	`jnl`	ProxNF: Neural Field Proximal Training for High-Resolution 4D Dynamic Image Reconstruction. IEEE Trans. Computational Imaging Luke Lozenski, Refik Mert Çam, Mark D. Pagel, Mark A. Anastasio, Umberto Villa
2024	J	`jnl`	Report on the AAPM Grand Challenge on deep generative modeling for learning medical image statistics. CoRR Rucha Deshpande, Varun A. Kelkar, Dimitrios S. Gotsis, Prabhat K. C., Rongping Zeng, Kyle J. Myers, Frank J. Brooks, Mark A. Anastasio
2023	J	`jnl`	AmbientFlow: Invertible generative models from incomplete, noisy measurements. CoRR Varun A. Kelkar, Rucha Deshpande, Arindam Banerjee, Mark A. Anastasio
2023	J	`jnl`	Assessing the Ability of Generative Adversarial Networks to Learn Canonical Medical Image Statistics. IEEE Trans. Medical Imaging Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Prabhat K. C., Kyle J. Myers, Rongping Zeng, Mark A. Anastasio
2023	J	`jnl`	Assessing the capacity of a denoising diffusion probabilistic model to reproduce spatial context. CoRR Rucha Deshpande, Muzaffer Özbey, Hua Li, Mark A. Anastasio, Frank J. Brooks
2023	—	`conf`	Estimating task-based performance bounds for image reconstruction methods by use of learned-ideal observers. Image Perception, Observer Performance, and Technology Assessment Kaiyan Li, Weimin Zhou, Hua Li, Mark A. Anastasio
2023	—	`conf`	Evaluating generative stochastic image models using task-based image quality measures. Image Perception, Observer Performance, and Technology Assessment Varun A. Kelkar, Dimitrios S. Gotsis, Rucha Deshpande, Frank J. Brooks, Prabhat K. C., Kyle J. Myers, Rongping Zeng, Mark A. Anastasio
2023	J	`jnl`	High-Dimensional MR Reconstruction Integrating Subspace and Adaptive Generative Models. CoRR Ruiyang Zhao, Xi Peng, Varun A. Kelkar, Mark A. Anastasio, Fan Lam
2023	J	`jnl`	Ideal Observer Computation by Use of Markov-Chain Monte Carlo With Generative Adversarial Networks. IEEE Trans. Medical Imaging Weimin Zhou, Umberto Villa, Mark A. Anastasio
2023	J	`jnl`	Ideal Observer Computation by Use of Markov-Chain Monte Carlo with Generative Adversarial Networks. CoRR Weimin Zhou, Umberto Villa, Mark A. Anastasio
2023	J	`jnl`	Revisiting model self-interpretability in a decision-theoretic way for binary medical image classification. CoRR Sourya Sengupta, Mark A. Anastasio
2023	—	`conf`	Semi-supervised contrastive learning for white blood cell segmentation from label-free quantitative phase imaging. Digital and Computational Pathology Sourya Sengupta, Michael John Fanous, Hua Li, Mark A. Anastasio
2023	J	`jnl`	The stochastic digital human is now enrolling for in silico imaging trials - Methods and tools for generating digital cohorts. CoRR Aldo Badano, Miguel A. Lago, Elena Sizikova, Jana G. Delfino, Shuyue Guan, Mark A. Anastasio, Berkman Sahiner
2022	J	`jnl`	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 Kaiyan Li, Weimin Zhou, Hua Li, Mark A. Anastasio
2022	J	`jnl`	A Memory-Efficient Self-Supervised Dynamic Image Reconstruction Method Using Neural Fields. IEEE Trans. Computational Imaging Luke Lozenski, Mark A. Anastasio, Umberto Villa
2022	—	`conf`	A task-informed model training method for deep neural network-based image denoising. Image Perception, Observer Performance, and Technology Assessment Kaiyan Li, Hua Li, Mark A. Anastasio
2022	—	`conf`	Analyzing neural networks applied to an anatomical simulation of the breast. Image Perception, Observer Performance, and Technology Assessment 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
2022	B	`conf`	Application of DatasetGAN in medical imaging: preliminary studies. Image Processing Zong Fan, Varun A. Kelkar, Mark A. Anastasio, Hua Li
2022	J	`jnl`	Application of DatasetGAN in medical imaging: preliminary studies. CoRR Zong Fan, Varun A. Kelkar, Mark A. Anastasio, Hua Li
2022	J	`jnl`	Assessing the ability of generative adversarial networks to learn canonical medical image statistics. CoRR Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Prabhat K. C., Kyle J. Myers, Rongping Zeng, Mark A. Anastasio
2022	J	`jnl`	Evaluating Procedures for Establishing Generative Adversarial Network-based Stochastic Image Models in Medical Imaging. CoRR Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Kyle J. Myers, Prabhat K. C., Rongping Zeng, Mark A. Anastasio
2022	—	`conf`	Evaluating procedures for establishing generative adversarial network-based stochastic image models in medical imaging. Image Perception, Observer Performance, and Technology Assessment Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Kyle J. Myers, Prabhat K. C., Rongping Zeng, Mark A. Anastasio
2022	B	`conf`	Evaluating the capacity of deep generative models to reproduce measurable high-order spatial arrangements in diagnostic images. Image Processing Rucha Deshpande, Mark A. Anastasio, Frank J. Brooks
2022	J	`jnl`	Investigating the robustness of a learning-based method for quantitative phase retrieval from propagation-based x-ray phase contrast measurements under laboratory conditions. CoRR Rucha Deshpande, Ashish Avachat, Frank J. Brooks, Mark A. Anastasio
2022	—	`conf`	Investigation of adversarial robust training for establishing interpretable CNN-based numerical observers. Image Perception, Observer Performance, and Technology Assessment Sourya Sengupta, Craig K. Abbey, Kaiyan Li, Mark A. Anastasio
2022	—	`conf`	Learned Hotelling observers for use with multi-modal data. Image Perception, Observer Performance, and Technology Assessment Jason L. Granstedt, Fu Li, Umberto Villa, Mark A. Anastasio
2022	J	`jnl`	Mining the manifolds of deep generative models for multiple data-consistent solutions of ill-posed tomographic imaging problems. CoRR Sayantan Bhadra, Umberto Villa, Mark A. Anastasio
2022	J	`jnl`	Prior image-based medical image reconstruction using a style-based generative adversarial network. CoRR Varun A. Kelkar, Mark A. Anastasio
2021	J	`jnl`	A Method for Evaluating the Capacity of Generative Adversarial Networks to Reproduce High-order Spatial Context. CoRR Rucha Deshpande, Mark A. Anastasio, Frank J. Brooks
2021	—	`conf`	A hybrid channelized Hotelling observer for estimating the ideal linear observer for total-variation-based image reconstruction. Image Perception, Observer Performance, and Technology Assessment John Paul Phillips, Emil Y. Sidky, Greg Ongie, Weimin Zhou, Juan-Pablo Cruz-Bastida, Ingrid S. Reiser, Mark A. Anastasio, Xiaochuan Pan
2021	—	`conf`	Advancing the AmbientGAN for learning stochastic object models. Image Perception, Observer Performance, and Technology Assessment Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Jason L. Granstedt, Hua Li, Mark A. Anastasio
2021	J	`jnl`	Advancing the AmbientGAN for learning stochastic object models. CoRR Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Jason L. Granstedt, Hua Li, Mark A. Anastasio
2021	—	`conf`	Assessing regularization in tomographic imaging via hallucinations in the null space. Image Perception, Observer Performance, and Technology Assessment Sayantan Bhadra, Varun A. Kelkar, Frank J. Brooks, Mark A. Anastasio
2021	J	`jnl`	Assessing the Impact of Deep Neural Network-Based Image Denoising on Binary Signal Detection Tasks. IEEE Trans. Medical Imaging Kaiyan Li, Weimin Zhou, Hua Li, Mark A. Anastasio
2021	J	`jnl`	Compressible Latent-Space Invertible Networks for Generative Model-Constrained Image Reconstruction. IEEE Trans. Computational Imaging Varun A. Kelkar, Sayantan Bhadra, Mark A. Anastasio
2021	J	`jnl`	Decoding visual information from high-density diffuse optical tomography neuroimaging data. NeuroImage 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
2021	J	`jnl`	Deeply-supervised density regression for automatic cell counting in microscopy images. Medical Image Anal. Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Mark A. Anastasio, Hua Li
2021	J	`jnl`	Impact of deep learning-based image super-resolution on binary signal detection. CoRR Xiaohui Zhang, Varun A. Kelkar, Jason L. Granstedt, Hua Li, Mark A. Anastasio
2021	J	`jnl`	Learning stochastic object models from medical imaging measurements by use of advanced AmbientGANs. CoRR Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio
2021	J	`jnl`	On Hallucinations in Tomographic Image Reconstruction. IEEE Trans. Medical Imaging Sayantan Bhadra, Varun A. Kelkar, Frank J. Brooks, Mark A. Anastasio
2021	A*	`conf`	Prior Image-Constrained Reconstruction using Style-Based Generative Models. ICML Varun A. Kelkar, Mark A. Anastasio
2021	J	`jnl`	Prior Image-Constrained Reconstruction using Style-Based Generative Models. CoRR Varun A. Kelkar, Mark A. Anastasio
2021	B	`conf`	SlabGAN: a method for generating efficient 3D anisotropic medical volumes using generative adversarial networks. Image Processing Jason L. Granstedt, Varun A. Kelkar, Weimin Zhou, Mark A. Anastasio
2021	—	`conf`	Supervised learning-based ideal observer approximation for joint detection and estimation tasks. Image Perception, Observer Performance, and Technology Assessment Kaiyan Li, Weimin Zhou, Hua Li, Mark A. Anastasio
2021	—	`conf`	Task-based evaluation of deep image super-resolution in medical imaging. Image Perception, Observer Performance, and Technology Assessment Varun A. Kelkar, Xiaohui Zhang, Jason L. Granstedt, Hua Li, Mark A. Anastasio
2021	—	`conf`	Task-based performance evaluation of deep neural network-based image denoising. Image Perception, Observer Performance, and Technology Assessment Kaiyan Li, Weimin Zhou, Hua Li, Mark A. Anastasio
2020	J	`jnl`	Approximating the Hotelling Observer with Autoencoder-Learned Efficient Channels for Binary Signal Detection Tasks. CoRR Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio
2020	J	`jnl`	Approximating the Ideal Observer for Joint Signal Detection and Localization Tasks by use of Supervised Learning Methods. IEEE Trans. Medical Imaging Weimin Zhou, Hua Li, Mark A. Anastasio
2020	J	`jnl`	Approximating the Ideal Observer for joint signal detection and localization tasks by use of supervised learning methods. CoRR Weimin Zhou, Hua Li, Mark A. Anastasio
2020	J	`jnl`	Deeply-Supervised Density Regression for Automatic Cell Counting in Microscopy Images. CoRR Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Mark A. Anastasio, Hua Li
2020	J	`jnl`	Learning Numerical Observers using Unsupervised Domain Adaptation. CoRR Shenghua He, Weimin Zhou, Hua Li, Mark A. Anastasio
2020	—	`conf`	Learning efficient channels with a dual loss autoencoder. Image Perception, Observer Performance, and Technology Assessment Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio
2020	—	`conf`	Learning numerical observers using unsupervised domain adaptation. Image Perception, Observer Performance, and Technology Assessment Shenghua He, Weimin Zhou, Hua Li, Mark A. Anastasio
2020	J	`jnl`	Learning stochastic object models from medical imaging measurements using Progressively-Growing AmbientGANs. CoRR Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio
2020	J	`jnl`	Markov-Chain Monte Carlo Approximation of the Ideal Observer using Generative Adversarial Networks. CoRR Weimin Zhou, Mark A. Anastasio
2020	—	`conf`	Markov-Chain Monte Carlo approximation of the Ideal Observer using generative adversarial networks. Image Perception, Observer Performance, and Technology Assessment Weimin Zhou, Mark A. Anastasio
2020	J	`jnl`	Medical image reconstruction with image-adaptive priors learned by use of generative adversarial networks. CoRR Sayantan Bhadra, Weimin Zhou, Mark A. Anastasio
2020	J	`jnl`	On hallucinations in tomographic image reconstruction. CoRR Sayantan Bhadra, Varun A. Kelkar, Frank J. Brooks, Mark A. Anastasio
2020	J	`jnl`	Progressively-Growing AmbientGANs For Learning Stochastic Object Models From Imaging Measurements. CoRR Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio
2020	—	`conf`	Progressively-Growing AmbientGANs for learning stochastic object models from imaging measurements. Image Perception, Observer Performance, and Technology Assessment Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio
2019	J	`jnl`	A survey of computational frameworks for solving the acoustic inverse problem in three-dimensional photoacoustic computed tomography. CoRR Joemini Poudel, Yang Lou, Mark A. Anastasio
2019	J	`jnl`	Analysis of the Use of Unmatched Backward Operators in Iterative Image Reconstruction With Application to Three-Dimensional Optoacoustic Tomography. IEEE Trans. Computational Imaging Yang Lou, Seonyeong Park, Fatima Anis, Richard Su, Alexander A. Oraevsky, Mark A. Anastasio
2019	J	`jnl`	Approximating the Ideal Observer and Hotelling Observer for Binary Signal Detection Tasks by Use of Supervised Learning Methods. IEEE Trans. Medical Imaging Weimin Zhou, Hua Li, Mark A. Anastasio
2019	J	`jnl`	Approximating the Ideal Observer and Hotelling Observer for binary signal detection tasks by use of supervised learning methods. CoRR Weimin Zhou, Hua Li, Mark A. Anastasio
2019	—	`conf`	Autoencoder embedding of task-specific information. Image Perception, Observer Performance, and Technology Assessment Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio
2019	—	`conf`	Automatic microscopic cell counting by use of deeply-supervised density regression model. Digital Pathology Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Mark A. Anastasio, Hua Li
2019	J	`jnl`	Automatic microscopic cell counting by use of deeply-supervised density regression model. CoRR Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Mark A. Anastasio, Hua Li
2019	—	`conf`	Automatic microscopic cell counting by use of unsupervised adversarial domain adaptation and supervised density regression. Digital Pathology Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Hua Li, Mark A. Anastasio
2019	J	`jnl`	Automatic microscopic cell counting by use of unsupervised adversarial domain adaptation and supervised density regression. CoRR Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Hua Li, Mark A. Anastasio
2019	—	`conf`	Learning stochastic object model from noisy imaging measurements using AmbientGANs. Image Perception, Observer Performance, and Technology Assessment Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Mark A. Anastasio
2019	—	`conf`	Learning the Hotelling observer for SKE detection tasks by use of supervised learning methods. Image Perception, Observer Performance, and Technology Assessment Weimin Zhou, Hua Li, Mark A. Anastasio
2019	—	`conf`	Learning the ideal observer for joint detection and localization tasks by use of convolutional neural networks. Image Perception, Observer Performance, and Technology Assessment Weimin Zhou, Mark A. Anastasio
2019	J	`jnl`	Reconstruction-Aware Imaging System Ranking by Use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference. IEEE Trans. Medical Imaging Yujia Chen, Yang Lou, Kun Wang, Matthew A. Kupinski, Mark A. Anastasio
2019	J	`jnl`	Reconstruction-Aware Imaging System Ranking by use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference. CoRR Yujia Chen, Yang Lou, Kun Wang, Matthew A. Kupinski, Mark A. Anastasio
2018	J	`jnl`	A deep Boltzmann machine-driven level set method for heart motion tracking using cine MRI images. Medical Image Anal. 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
2018	—	`conf`	Active learning with noise modeling for medical image annotation. ISBI Jian Wu, Su Ruan, Chunfeng Lian, Sasa Mutic, Mark A. Anastasio, Hua Li
2018	B	`conf`	Convolutional neural network based automatic plaque characterization for intracoronary optical coherence tomography images. Image Processing Shenghua He, Jie Zheng, Akiko Maehara, Gary S. Mintz, Dalin Tang, Mark A. Anastasio, Hua Li
2018	J	`jnl`	Convolutional neural network based automatic plaque characterization from intracoronary optical coherence tomography images. CoRR Shenghua He, Jie Zheng, Akiko Maehara, Gary S. Mintz, Dalin Tang, Mark A. Anastasio, Hua Li
2018	—	`conf`	Heart motion tracking on cine MRI based on a deep Boltzmann machine-driven level set method. ISBI 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
2018	—	`conf`	Learning the ideal observer for SKE detection tasks by use of convolutional neural networks. Image Perception, Observer Performance, and Technology Assessment Weimin Zhou, Mark A. Anastasio
2018	J	`jnl`	Parameterized Joint Reconstruction of the Initial Pressure and Sound Speed Distributions for Photoacoustic Computed Tomography. SIAM J. Imaging Sci. Thomas P. Matthews, Joemini Poudel, Lei Li, Lihong V. Wang, Mark A. Anastasio
2017	J	`jnl`	A Forward-Adjoint Operator Pair Based on the Elastic Wave Equation for Use in Transcranial Photoacoustic Computed Tomography. SIAM J. Imaging Sci. Kenji Mitsuhashi, Joemini Poudel, Thomas P. Matthews, Alejandro Garcia-Uribe, Lihong V. Wang, Mark A. Anastasio
2017	J	`jnl`	Deep Learning-Guided Image Reconstruction from Incomplete Data. CoRR Brendan Kelly, Thomas P. Matthews, Mark A. Anastasio
2016	J	`jnl`	Joint Reconstruction of Absorbed Optical Energy Density and Sound Speed Distributions in Photoacoustic Computed Tomography: A Numerical Investigation. IEEE Trans. Computational Imaging Chao Huang, Kun Wang, Robert W. Schoonover, Lihong V. Wang, Mark A. Anastasio
2015	—	`ch.`	Photoacoustic and Thermoacoustic Tomography: Image Formation Principles. Handbook of Mathematical Methods in Imaging Kun Wang, Mark A. Anastasio
2014	J	`jnl`	Discrete Imaging Models for Three-Dimensional Optoacoustic Tomography Using Radially Symmetric Expansion Functions. IEEE Trans. Medical Imaging Kun Wang, Robert W. Schoonover, Richard Su, Alexander A. Oraevsky, Mark A. Anastasio
2014	J	`jnl`	Proximal ADMM for Multi-Channel Image Reconstruction in Spectral X-ray CT. IEEE Trans. Medical Imaging Alex Sawatzky, Qiaofeng Xu, Carsten Oliver Schirra, Mark A. Anastasio
2013	J	`jnl`	Full-Wave Iterative Image Reconstruction in Photoacoustic Tomography With Acoustically Inhomogeneous Media. IEEE Trans. Medical Imaging Chao Huang, Kun Wang, Liming Nie, Lihong V. Wang, Mark A. Anastasio
2013	J	`jnl`	Statistical Reconstruction of Material Decomposed Data in Spectral CT. IEEE Trans. Medical Imaging Carsten Oliver Schirra, Ewald Roessl, Thomas Köhler, Bernhard Brendel, Axel Thran, Dipanjan Pan, Mark A. Anastasio, Roland Proksa
2011	J	`jnl`	An Imaging Model Incorporating Ultrasonic Transducer Properties for Three-Dimensional Optoacoustic Tomography. IEEE Trans. Medical Imaging Kun Wang, Sergey A. Ermilov, Richard Su, Hans-Peter Brecht, Alexander A. Oraevsky, Mark A. Anastasio
2009	J	`jnl`	Effects of Different Imaging Models on Least-Squares Image Reconstruction Accuracy in Photoacoustic Tomography. IEEE Trans. Medical Imaging Jin Zhang, Mark A. Anastasio, Patrick J. La Rivière, Lihong V. Wang
2009	J	`jnl`	Relationships Between Smooth- and Small-Phase Conditions in X-Ray Phase-Contrast Imaging. IEEE Trans. Medical Imaging Daxin Shi, Mark A. Anastasio
2006	—	`conf`	Progress in multiple-image radiography. Computational Imaging Miles N. Wernick, Jovan G. Brankov, Dean Chapman, Yongyi Yang, Gocha Khelashvili, Mark A. Anastasio, Zhong Zhong, Christopher Parham, Jun Li, Carol Muehleman
2005	J	`jnl`	Feasibility of half-data image reconstruction in 3-D reflectivity tomography with a spherical aperture. IEEE Trans. Medical Imaging Mark A. Anastasio, Jin Zhang, Emil Y. Sidky, Yu Zou, Dan Xia, Xiaochuan Pan
2005	J	`jnl`	Half-time image reconstruction in thermoacoustic tomography. IEEE Trans. Medical Imaging Mark A. Anastasio, Jin Zhang, Xiaochuan Pan, Yu Zou, Geng Ku, Lihong V. Wang
2005	J	`jnl`	Weighted expectation maximization reconstruction algorithms for thermoacoustic tomography. IEEE Trans. Medical Imaging Jin Zhang, Mark A. Anastasio, Xiaochuan Pan, Lihong V. Wang
2004	—	`conf`	Multiple-Image Computed Tomography. ISBI Miles N. Wernick, Jovan G. Brankov, Dean Chapman, Mark A. Anastasio, Zhong Zhong, Carol Muehleman, Jun Li
2003	J	`jnl`	An improved reconstruction algorithm for 3-D diffraction tomography using spherical-wave sources. IEEE Trans. Biomed. Eng. Mark A. Anastasio, Xiaochuan Pan
2003	J	`jnl`	Data redundancy and reduced-scan reconstruction in reflectivity tomography. IEEE Trans. Image Process. Xiaochuan Pan, Yu Zou, Mark A. Anastasio
2003	—	`conf`	Investigation of megavoltage local tomography for detecting setup errors in radiation therapy. Image-Guided Procedures Daxin Shi, Mark A. Anastasio, Xiaochuan Pan, Charles A. Pelizzari, Peter Munro
2002	—	`conf`	Image reconstruction of reflectivity from short scan data. ISBI Xiaochuan Pan, Yu Zou, Mark A. Anastasio
2002	J	`jnl`	Numerically robust minimal-scan reconstruction algorithms for diffraction tomography via radon transform inversion. Int. J. Imaging Syst. Technol. Mark A. Anastasio, Xiaochuan Pan
2002	J	`jnl`	On a limited-view reconstruction problem in wavefield tomography. IEEE Trans. Medical Imaging Xiaochuan Pan, Mark A. Anastasio
2001	J	`jnl`	Comments on the Filtered Backprojection Algorithm, Range Conditions, and the Pseudoinverse Solution. IEEE Trans. Medical Imaging Mark A. Anastasio, Xiaochuan Pan, Eric Clarkson
2001	B	`conf`	Development and evaluation of minimal-scan reconstruction algorithms for diffraction tomography. Image Processing Mark A. Anastasio, Xiaochuan Pan
2000	J	`jnl`	A new reconstruction approach for reflection mode diffraction tomography. IEEE Trans. Image Process. Mark A. Anastasio, Xiaochuan Pan
2000	B	`conf`	Multiobjective genetic optimization of diagnostic classifiers used in the computerized detection of mass lesions in mammography. Image Processing Matthew A. Kupinski, Mark A. Anastasio, Maryellen Lissak Giger
1999	J	`jnl`	Investigation of the noise properties of a new class of reconstruction methods in diffraction tomography. Int. J. Imaging Syst. Technol. Mark A. Anastasio, Xiaochuan Pan
1999	J	`jnl`	Multidimensional smoothing using orthogonal expansions. IEEE Signal Process. Lett. Mark A. Anastasio, Xiaochuan Pan, Chien-Min Kao
1999	J	`jnl`	Multiobjective Genetic Optimization of Diagnostic Classifiers with Implications for Generating ROC Curves. IEEE Trans. Medical Imaging Matthew A. Kupinski, Mark A. Anastasio
1998	—	`conf`	A General Technique for Smoothing Multi-Dimensional Datasets Utilizing Orthogonal Expansions and Lower Dimensional Smoothers. ICIP (2) Mark A. Anastasio, Xiaochuan Pan, Chien-Min Kao
1998	J	`jnl`	Optimization and FROC Analysis of Rule-Based Detection Schemes Using a Multiobjective Approach. IEEE Trans. Medical Imaging Mark A. Anastasio, Matthew A. Kupinski, Robert M. Nishikawa