Mark A. Anastasio
Orcid: 0000-0002-3192-4172
According to our database1,
Mark A. Anastasio
authored at least 93 papers
between 1998 and 2024.
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Bibliography
2024
Learned Full Waveform Inversion Incorporating Task Information for Ultrasound Computed Tomography.
IEEE Trans. Computational Imaging, 2024
2023
Ideal Observer Computation by Use of Markov-Chain Monte Carlo With Generative Adversarial Networks.
IEEE Trans. Medical Imaging, December, 2023
Assessing the Ability of Generative Adversarial Networks to Learn Canonical Medical Image Statistics.
IEEE Trans. Medical Imaging, June, 2023
Assessing the capacity of a denoising diffusion probabilistic model to reproduce spatial context.
CoRR, 2023
CoRR, 2023
High-Dimensional MR Reconstruction Integrating Subspace and Adaptive Generative Models.
CoRR, 2023
Revisiting model self-interpretability in a decision-theoretic way for binary medical image classification.
CoRR, 2023
Evaluating generative stochastic image models using task-based image quality measures.
Proceedings of the Medical Imaging 2023: Image Perception, 2023
Estimating task-based performance bounds for image reconstruction methods by use of learned-ideal observers.
Proceedings of the Medical Imaging 2023: Image Perception, 2023
2022
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, 2022
A Memory-Efficient Self-Supervised Dynamic Image Reconstruction Method Using Neural Fields.
IEEE Trans. Computational Imaging, 2022
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
Prior image-based medical image reconstruction using a style-based generative adversarial network.
CoRR, 2022
Mining the manifolds of deep generative models for multiple data-consistent solutions of ill-posed tomographic imaging problems.
CoRR, 2022
Investigation of adversarial robust training for establishing interpretable CNN-based numerical observers.
Proceedings of the Medical Imaging 2022: Image Perception, 2022
Evaluating procedures for establishing generative adversarial network-based stochastic image models in medical imaging.
Proceedings of the Medical Imaging 2022: Image Perception, 2022
Proceedings of the Medical Imaging 2022: Image Perception, 2022
Proceedings of the Medical Imaging 2022: Image Perception, 2022
Proceedings of the Medical Imaging 2022: Image Perception, 2022
Proceedings of the Medical Imaging 2022: Image Processing, 2022
Evaluating the capacity of deep generative models to reproduce measurable high-order spatial arrangements in diagnostic images.
Proceedings of the Medical Imaging 2022: Image Processing, 2022
2021
IEEE Trans. Medical Imaging, 2021
Assessing the Impact of Deep Neural Network-Based Image Denoising on Binary Signal Detection Tasks.
IEEE Trans. Medical Imaging, 2021
Compressible Latent-Space Invertible Networks for Generative Model-Constrained Image Reconstruction.
IEEE Trans. Computational Imaging, 2021
Decoding visual information from high-density diffuse optical tomography neuroimaging data.
NeuroImage, 2021
Deeply-supervised density regression for automatic cell counting in microscopy images.
Medical Image Anal., 2021
A Method for Evaluating the Capacity of Generative Adversarial Networks to Reproduce High-order Spatial Context.
CoRR, 2021
CoRR, 2021
Learning stochastic object models from medical imaging measurements by use of advanced AmbientGANs.
CoRR, 2021
Proceedings of the Medical Imaging 2021: Image Perception, 2021
A hybrid channelized Hotelling observer for estimating the ideal linear observer for total-variation-based image reconstruction.
Proceedings of the Medical Imaging 2021: Image Perception, 2021
Proceedings of the Medical Imaging 2021: Image Perception, 2021
Assessing regularization in tomographic imaging via hallucinations in the null space.
Proceedings of the Medical Imaging 2021: Image Perception, 2021
Proceedings of the Medical Imaging 2021: Image Perception, 2021
Supervised learning-based ideal observer approximation for joint detection and estimation tasks.
Proceedings of the Medical Imaging 2021: Image Perception, 2021
SlabGAN: a method for generating efficient 3D anisotropic medical volumes using generative adversarial networks.
Proceedings of the Medical Imaging 2021: Image Processing, Online, February 15-19, 2021, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
2020
Approximating the Ideal Observer for Joint Signal Detection and Localization Tasks by use of Supervised Learning Methods.
IEEE Trans. Medical Imaging, 2020
Learning stochastic object models from medical imaging measurements using Progressively-Growing AmbientGANs.
CoRR, 2020
Approximating the Hotelling Observer with Autoencoder-Learned Efficient Channels for Binary Signal Detection Tasks.
CoRR, 2020
Medical image reconstruction with image-adaptive priors learned by use of generative adversarial networks.
CoRR, 2020
Progressively-Growing AmbientGANs for learning stochastic object models from imaging measurements.
Proceedings of the Medical Imaging 2020: Image Perception, 2020
Markov-Chain Monte Carlo approximation of the Ideal Observer using generative adversarial networks.
Proceedings of the Medical Imaging 2020: Image Perception, 2020
Proceedings of the Medical Imaging 2020: Image Perception, 2020
Proceedings of the Medical Imaging 2020: Image Perception, 2020
2019
Approximating the Ideal Observer and Hotelling Observer for Binary Signal Detection Tasks by Use of Supervised Learning Methods.
IEEE Trans. Medical Imaging, 2019
Reconstruction-Aware Imaging System Ranking by Use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference.
IEEE Trans. Medical Imaging, 2019
Analysis of the Use of Unmatched Backward Operators in Iterative Image Reconstruction With Application to Three-Dimensional Optoacoustic Tomography.
IEEE Trans. Computational Imaging, 2019
A survey of computational frameworks for solving the acoustic inverse problem in three-dimensional photoacoustic computed tomography.
CoRR, 2019
Proceedings of the Medical Imaging 2019: Image Perception, 2019
Learning the ideal observer for joint detection and localization tasks by use of convolutional neural networks.
Proceedings of the Medical Imaging 2019: Image Perception, 2019
Learning the Hotelling observer for SKE detection tasks by use of supervised learning methods.
Proceedings of the Medical Imaging 2019: Image Perception, 2019
Proceedings of the Medical Imaging 2019: Image Perception, 2019
Automatic microscopic cell counting by use of deeply-supervised density regression model.
Proceedings of the Medical Imaging 2019: Digital Pathology, 2019
Automatic microscopic cell counting by use of unsupervised adversarial domain adaptation and supervised density regression.
Proceedings of the Medical Imaging 2019: Digital Pathology, 2019
2018
Parameterized Joint Reconstruction of the Initial Pressure and Sound Speed Distributions for Photoacoustic Computed Tomography.
SIAM J. Imaging Sci., 2018
A deep Boltzmann machine-driven level set method for heart motion tracking using cine MRI images.
Medical Image Anal., 2018
Convolutional neural network based automatic plaque characterization from intracoronary optical coherence tomography images.
CoRR, 2018
Learning the ideal observer for SKE detection tasks by use of convolutional neural networks.
Proceedings of the Medical Imaging 2018: Image Perception, 2018
Convolutional neural network based automatic plaque characterization for intracoronary optical coherence tomography images.
Proceedings of the Medical Imaging 2018: Image Processing, 2018
Heart motion tracking on cine MRI based on a deep Boltzmann machine-driven level set method.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018
2017
A Forward-Adjoint Operator Pair Based on the Elastic Wave Equation for Use in Transcranial Photoacoustic Computed Tomography.
SIAM J. Imaging Sci., 2017
2016
Joint Reconstruction of Absorbed Optical Energy Density and Sound Speed Distributions in Photoacoustic Computed Tomography: A Numerical Investigation.
IEEE Trans. Computational Imaging, 2016
2015
Proceedings of the Handbook of Mathematical Methods in Imaging, 2015
2014
Discrete Imaging Models for Three-Dimensional Optoacoustic Tomography Using Radially Symmetric Expansion Functions.
IEEE Trans. Medical Imaging, 2014
IEEE Trans. Medical Imaging, 2014
2013
IEEE Trans. Medical Imaging, 2013
Full-Wave Iterative Image Reconstruction in Photoacoustic Tomography With Acoustically Inhomogeneous Media.
IEEE Trans. Medical Imaging, 2013
2011
An Imaging Model Incorporating Ultrasonic Transducer Properties for Three-Dimensional Optoacoustic Tomography.
IEEE Trans. Medical Imaging, 2011
2009
Effects of Different Imaging Models on Least-Squares Image Reconstruction Accuracy in Photoacoustic Tomography.
IEEE Trans. Medical Imaging, 2009
Relationships Between Smooth- and Small-Phase Conditions in X-Ray Phase-Contrast Imaging.
IEEE Trans. Medical Imaging, 2009
2006
Proceedings of the Computational Imaging IV, San Jose, 2006
2005
Weighted expectation maximization reconstruction algorithms for thermoacoustic tomography.
IEEE Trans. Medical Imaging, 2005
Feasibility of half-data image reconstruction in 3-D reflectivity tomography with a spherical aperture.
IEEE Trans. Medical Imaging, 2005
IEEE Trans. Medical Imaging, 2005
2004
Proceedings of the 2004 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2004
2003
IEEE Trans. Image Process., 2003
An improved reconstruction algorithm for 3-D diffraction tomography using spherical-wave sources.
IEEE Trans. Biomed. Eng., 2003
Investigation of megavoltage local tomography for detecting setup errors in radiation therapy.
Proceedings of the Medical Imaging 2003: Visualization, 2003
2002
IEEE Trans. Medical Imaging, 2002
Numerically robust minimal-scan reconstruction algorithms for diffraction tomography via radon transform inversion.
Int. J. Imaging Syst. Technol., 2002
Proceedings of the 2002 IEEE International Symposium on Biomedical Imaging, 2002
2001
Comments on the Filtered Backprojection Algorithm, Range Conditions, and the Pseudoinverse Solution.
IEEE Trans. Medical Imaging, 2001
Development and evaluation of minimal-scan reconstruction algorithms for diffraction tomography.
Proceedings of the Medical Imaging 2001: Image Processing, 2001
2000
IEEE Trans. Image Process., 2000
Multiobjective genetic optimization of diagnostic classifiers used in the computerized detection of mass lesions in mammography.
Proceedings of the Medical Imaging 2000: Image Processing, 2000
1999
Multiobjective Genetic Optimization of Diagnostic Classifiers with Implications for Generating ROC Curves.
IEEE Trans. Medical Imaging, 1999
IEEE Signal Process. Lett., 1999
Investigation of the noise properties of a new class of reconstruction methods in diffraction tomography.
Int. J. Imaging Syst. Technol., 1999
1998
Optimization and FROC Analysis of Rule-Based Detection Schemes Using a Multiobjective Approach.
IEEE Trans. Medical Imaging, 1998
A General Technique for Smoothing Multi-Dimensional Datasets Utilizing Orthogonal Expansions and Lower Dimensional Smoothers.
Proceedings of the 1998 IEEE International Conference on Image Processing, 1998