Search Results for author: Gregery T. Buzzard

Found 20 papers, 1 papers with code

MACE CT Reconstruction for Modular Material Decomposition from Energy Resolving Photon-Counting Data

no code implementations1 Feb 2024 Natalie M. Jadue, Madhuri Nagare, Jonathan S. Maltz, Gregery T. Buzzard, Charles A. Bouman

Current commercial and prototype clinical photon counting CT systems utilize PCD-CT reconstruction methods that either reconstruct from each spectral bin separately, or first create an estimate of a material sinogram using a specified set of basis materials and then reconstruct from these material sinograms.

Computed Tomography (CT)

Texture Matching GAN for CT Image Enhancement

no code implementations20 Dec 2023 Madhuri Nagare, Gregery T. Buzzard, Charles A. Bouman

However, naive application of DNN-based methods can result in image texture that is undesirable in clinical applications.

Computed Tomography (CT) Generative Adversarial Network +1

Generative Plug and Play: Posterior Sampling for Inverse Problems

1 code implementation12 Jun 2023 Charles A. Bouman, Gregery T. Buzzard

In this paper, we introduce Generative Plug-and-Play (GPnP), a generalization of PnP to sample from the posterior distribution.

Image Denoising

Dynamic DH-MBIR for Phase-Error Estimation from Streaming Digital-Holography Data

no code implementations5 May 2023 Ali G. Sheikh, Casey J. Pellizzari, Sherman J. Kisner, Gregery T. Buzzard, Charles A. Bouman

These phase error estimates must be computed with very low latency to keep pace with changing atmospheric parameters, which requires that phase errors be estimated in a single shot of DH data.

X-ray Spectral Estimation using Dictionary Learning

no code implementations27 Feb 2023 Wenrui Li, Venkatesh Sridhar, K. Aditya Mohan, Saransh Singh, Jean-Baptiste Forien, Xin Liu, Gregery T. Buzzard, Charles A. Bouman

As computational tools for X-ray computed tomography (CT) become more quantitatively accurate, knowledge of the source-detector spectral response is critical for quantitative system-independent reconstruction and material characterization capabilities.

Computed Tomography (CT) Dictionary Learning

Autonomous Polycrystalline Material Decomposition for Hyperspectral Neutron Tomography

no code implementations27 Feb 2023 Mohammad Samin Nur Chowdhury, Diyu Yang, Shimin Tang, Singanallur V. Venkatakrishnan, Hassina Z. Bilheux, Gregery T. Buzzard, Charles A. Bouman

The algorithm estimates the linear attenuation coefficient spectra from the measured radiographs and then uses these spectra to perform polycrystalline material decomposition and reconstructs 3D material volumes to localize materials in the spatial domain.

Ringing Artifact Reduction Method for Ultrasound Reconstruction Using Multi-Agent Consensus Equilibrium

no code implementations9 Feb 2023 Abdulrahman M. Alanazi, Singanallur Venkatakrishnan, Gregery T. Buzzard, Charles A. Bouman

Our approach integrates a physics-based forward model that accounts for the propagation of a collimated ultrasonic beam in multi-layered media, a spatially varying image prior, and a denoiser designed to suppress the ringing artifacts that are characteristic of reconstructions from high-fractional bandwidth ultrasound sensor data.

Image Reconstruction

An Edge Alignment-based Orientation Selection Method for Neutron Tomography

no code implementations1 Dec 2022 Diyu Yang, Shimin Tang, Singanallur V. Venkatakrishnan, Mohammad S. N. Chowdhury, Yuxuan Zhang, Hassina Z. Bilheux, Gregery T. Buzzard, Charles A. Bouman

Neutron computed tomography (nCT) is a 3D characterization technique used to image the internal morphology or chemical composition of samples in biology and materials sciences.

Model-based Reconstruction for Multi-Frequency Collimated Beam Ultrasound Systems

no code implementations29 Nov 2022 Abdulrahman M. Alanazi, Singanallur Venkatakrishnan, Hector Santos-Villalobos, Gregery T. Buzzard, Charles Bouman

Collimated beam ultrasound systems are a technology for imaging inside multi-layered structures such as geothermal wells.

Multi-Pose Fusion for Sparse-View CT Reconstruction Using Consensus Equilibrium

no code implementations15 Sep 2022 Diyu Yang, Craig A. J. Kemp, Gregery T. Buzzard, Charles A. Bouman

In this paper, we present Multi-Pose Fusion, a novel algorithm that performs a joint tomographic reconstruction from CT scans acquired from multiple poses of a single object, where each pose has a distinct rotation axis.

Plug-and-Play Methods for Integrating Physical and Learned Models in Computational Imaging

no code implementations31 Mar 2022 Ulugbek S. Kamilov, Charles A. Bouman, Gregery T. Buzzard, Brendt Wohlberg

Plug-and-Play Priors (PnP) is one of the most widely-used frameworks for solving computational imaging problems through the integration of physical models and learned models.

Sparse-View CT Reconstruction using Recurrent Stacked Back Projection

no code implementations9 Dec 2021 Wenrui Li, Gregery T. Buzzard, Charles A. Bouman

Sparse-view CT reconstruction is important in a wide range of applications due to limitations on cost, acquisition time, or dosage.

Projected Multi-Agent Consensus Equilibrium for Ptychographic Image Reconstruction

no code implementations28 Nov 2021 Qiuchen Zhai, Brendt Wohlberg, Gregery T. Buzzard, Charles A. Bouman

Ptychography is a computational imaging technique using multiple, overlapping, coherently illuminated snapshots to achieve nanometer resolution by solving a nonlinear phase-field recovery problem.

Image Reconstruction

Multi-Slice Fusion for Sparse-View and Limited-Angle 4D CT Reconstruction

no code implementations1 Aug 2020 Soumendu Majee, Thilo Balke, Craig A. J. Kemp, Gregery T. Buzzard, Charles A. Bouman

In this paper, we present multi-slice fusion, a novel algorithm for 4D reconstruction, based on the fusion of multiple low-dimensional denoisers.

4D reconstruction Denoising

Safe Approximate Dynamic Programming Via Kernelized Lipschitz Estimation

no code implementations3 Jul 2019 Ankush Chakrabarty, Devesh K. Jha, Gregery T. Buzzard, Yebin Wang, Kyriakos Vamvoudakis

We develop a method for obtaining safe initial policies for reinforcement learning via approximate dynamic programming (ADP) techniques for uncertain systems evolving with discrete-time dynamics.

reinforcement-learning Reinforcement Learning (RL)

4D X-Ray CT Reconstruction using Multi-Slice Fusion

no code implementations15 Jun 2019 Soumendu Majee, Thilo Balke, Craig A. J. Kemp, Gregery T. Buzzard, Charles A. Bouman

In this paper, we present Multi-Slice Fusion, a novel algorithm for 4D and higher-dimensional reconstruction, based on the fusion of multiple low-dimensional denoisers.

4D reconstruction Denoising +1

Deep Back Projection for Sparse-View CT Reconstruction

no code implementations6 Jul 2018 Dong Hye Ye, Gregery T. Buzzard, Max Ruby, Charles A. Bouman

Filtered back projection (FBP) is a classical method for image reconstruction from sinogram CT data.

Image Reconstruction

Plug-and-Play Unplugged: Optimization Free Reconstruction using Consensus Equilibrium

no code implementations24 May 2017 Gregery T. Buzzard, Stanley H. Chan, Suhas Sreehari, Charles A. Bouman

We give examples to illustrate consensus equilibrium and the convergence properties of these algorithms and demonstrate this method on some toy problems and on a denoising example in which we use an array of convolutional neural network denoisers, none of which is tuned to match the noise level in a noisy image but which in consensus can achieve a better result than any of them individually.

Denoising Image Reconstruction

A Framework for Dynamic Image Sampling Based on Supervised Learning (SLADS)

no code implementations14 Mar 2017 G. M. Dilshan P. Godaliyadda, Dong Hye Ye, Michael D. Uchic, Michael A. Groeber, Gregery T. Buzzard, Charles A. Bouman

In each step of SLADS, the objective is to find the pixel that maximizes the expected reduction in distortion (ERD) given previous measurements.

regression

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