Mark A. Anastasio

ORCID

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 86

Top Venues

CoRR

Medical Imaging: Image Perception, Observer Performance, and Technology Assessment

IEEE Trans. Medical Imaging

IEEE Trans. Computational Imaging

Publications

Zhuchen Shao, Mark A. Anastasio, Hua Li
Prior-guided Diffusion Model for Cell Segmentation in Quantitative Phase Imaging. CoRR (2024)
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 (2024)
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) (2024)
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 (2024)
Varun A. Kelkar, Rucha Deshpande, Arindam Banerjee, Mark A. Anastasio
AmbientFlow: Invertible generative models from incomplete, noisy measurements. Trans. Mach. Learn. Res. 2024 (2024)
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) (2024)
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) (2023)
Weimin Zhou, Umberto Villa, Mark A. Anastasio
Ideal Observer Computation by Use of Markov-Chain Monte Carlo with Generative Adversarial Networks. CoRR (2023)
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 (2023)
Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Prabhat KC, 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) (2023)
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)
Ruiyang Zhao, Xi Peng, Varun A. Kelkar, Mark A. Anastasio, Fan Lam
High-Dimensional MR Reconstruction Integrating Subspace and Adaptive Generative Models. CoRR (2023)
Varun A. Kelkar, Rucha Deshpande, Arindam Banerjee, Mark A. Anastasio
AmbientFlow: Invertible generative models from incomplete, noisy measurements. CoRR (2023)
Sourya Sengupta, Mark A. Anastasio
Revisiting model self-interpretability in a decision-theoretic way for binary medical image classification. CoRR (2023)
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)
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)
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)
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 (2022)
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)
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) (2022)
Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Kyle J. Myers, Prabhat KC, Rongping Zeng, Mark A. Anastasio
Evaluating Procedures for Establishing Generative Adversarial Network-based Stochastic Image Models in Medical Imaging. CoRR (2022)
Varun A. Kelkar, Mark A. Anastasio
Prior image-based medical image reconstruction using a style-based generative adversarial network. CoRR (2022)
Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Prabhat KC, Kyle J. Myers, Rongping Zeng, Mark A. Anastasio
Assessing the ability of generative adversarial networks to learn canonical medical image statistics. CoRR (2022)
Zong Fan, Varun A. Kelkar, Mark A. Anastasio, Hua Li
Application of DatasetGAN in medical imaging: preliminary studies. Medical Imaging: Image Processing (2022)
Luke Lozenski, Mark A. Anastasio, Umberto Villa
A Memory-Efficient Self-Supervised Dynamic Image Reconstruction Method Using Neural Fields. IEEE Trans. Computational Imaging 8 (2022)
Zong Fan, Varun A. Kelkar, Mark A. Anastasio, Hua Li
Application of DatasetGAN in medical imaging: preliminary studies. CoRR (2022)
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 (2022)
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)
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)
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)
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 (2021)
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)
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 (2021)
Sayantan Bhadra, Varun A. Kelkar, Frank J. Brooks, Mark A. Anastasio
On Hallucinations in Tomographic Image Reconstruction. IEEE Trans. Medical Imaging 40 (11) (2021)
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)
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)
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)
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)
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)
Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Jason L. Granstedt, Hua Li, Mark A. Anastasio
Advancing the AmbientGAN for learning stochastic object models. CoRR (2021)
Varun A. Kelkar, Mark A. Anastasio
Prior Image-Constrained Reconstruction using Style-Based Generative Models. ICML (2021)
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 (2021)
Varun A. Kelkar, Sayantan Bhadra, Mark A. Anastasio
Compressible Latent-Space Invertible Networks for Generative Model-Constrained Image Reconstruction. IEEE Trans. Computational Imaging 7 (2021)
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 (2021)
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)
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 (2021)
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) (2021)
Varun A. Kelkar, Mark A. Anastasio
Prior Image-Constrained Reconstruction using Style-Based Generative Models. CoRR (2021)
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 (2020)
Sayantan Bhadra, Varun A. Kelkar, Frank J. Brooks, Mark A. Anastasio
On hallucinations in tomographic image reconstruction. CoRR (2020)
Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio
Progressively-Growing AmbientGANs For Learning Stochastic Object Models From Imaging Measurements. CoRR (2020)
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)
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)
Sayantan Bhadra, Weimin Zhou, Mark A. Anastasio
Medical image reconstruction with image-adaptive priors learned by use of generative adversarial networks. CoRR (2020)
Weimin Zhou, Mark A. Anastasio
Markov-Chain Monte Carlo Approximation of the Ideal Observer using Generative Adversarial Networks. CoRR (2020)
Shenghua He, Weimin Zhou, Hua Li, Mark A. Anastasio
Learning Numerical Observers using Unsupervised Domain Adaptation. CoRR (2020)
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 (2020)
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 (2020)
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) (2020)
Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio
Approximating the Hotelling Observer with Autoencoder-Learned Efficient Channels for Binary Signal Detection Tasks. CoRR (2020)
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)
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)
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)
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)
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 (2019)
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) (2019)
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)
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 (2019)
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)
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) (2019)
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)
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 (2019)
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 (2019)
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 (2019)
Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio
Autoencoder embedding of task-specific information. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2019)
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) (2019)
Jian Wu, Su Ruan, Chunfeng Lian, Sasa Mutic, Mark A. Anastasio, Hua Li
Active learning with noise modeling for medical image annotation. ISBI (2018)
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 (2018)
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) (2018)
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)
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)
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)
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 (2018)
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) (2017)
Brendan Kelly, Thomas P. Matthews, Mark A. Anastasio
Deep Learning-Guided Image Reconstruction from Incomplete Data. CoRR (2017)
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) (2016)
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) (2014)
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) (2014)
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) (2013)
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) (2013)
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) (2011)
Daxin Shi, Mark A. Anastasio
Relationships Between Smooth- and Small-Phase Conditions in X-Ray Phase-Contrast Imaging. IEEE Trans. Medical Imaging 28 (12) (2009)
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) (2009)
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)
Jin Zhang, Mark A. Anastasio, Xiaochuan Pan, Lihong V. Wang
Weighted expectation maximization reconstruction algorithms for thermoacoustic tomography. IEEE Trans. Medical Imaging 24 (6) (2005)
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) (2005)
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) (2005)
Miles N. Wernick, Jovan G. Brankov, Dean Chapman, Mark A. Anastasio, Zhong Zhong, Carol Muehleman, Jun Li
Multiple-Image Computed Tomography. ISBI (2004)
Mark A. Anastasio, Xiaochuan Pan
An improved reconstruction algorithm for 3-D diffraction tomography using spherical-wave sources. IEEE Trans. Biomed. Eng. 50 (4) (2003)
Xiaochuan Pan, Yu Zou, Mark A. Anastasio
Data redundancy and reduced-scan reconstruction in reflectivity tomography. IEEE Trans. Image Process. 12 (7) (2003)

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Publication Activity (10 Years)

Top Topics

Top Venues

Mark A. Anastasio