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Learned Primal-Dual Reconstruction

https://doi.org/10.1109/tmi.2018.2799231

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging

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Approximation capabilities of multilayer feedforward networks

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Analytic Tomography

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Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle–Pock algorithm

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A Perspective on Deep Imaging

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Deep Residual Learning for Image Recognition

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Image quality assessment: from error visibility to structural similarity

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Deep Convolutional Neural Network for Inverse Problems in Imaging

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Low-Dose X-ray CT Reconstruction via Dictionary Learning

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TU-FG-207A-04: Overview of the Low Dose CT Grand Challenge

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FlexISP

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Fast and flexible X-ray tomography using the ASTRA toolbox

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Probabilistic Materials Informatics

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Deep learning based reconstruction methods for electrical impedance tomography

inferred← citeshttps://doi.org/10.1016/bs.hna.2026.03.003openalex-snapshot

Self-supervised deep learning for inverse imaging problems

inferred← citeshttps://doi.org/10.1016/bs.hna.2026.03.004openalex-snapshot

Deep image prior for computed tomography reconstruction

inferred← citeshttps://doi.org/10.1016/bs.hna.2026.05.002openalex-snapshot

Learned iterative networks

inferred← citeshttps://doi.org/10.1016/j.acha.2021.12.007openalex-snapshot

Deep microlocal reconstruction for limited-angle tomography

inferred← citeshttps://doi.org/10.1016/j.actamat.2023.118966openalex-snapshot

Local-Global Decompositions for Conditional Microstructure Generation

inferred← citeshttps://doi.org/10.1016/j.actamat.2024.119877openalex-snapshot

Inverse Stochastic Microstructure Design

inferred← citeshttps://doi.org/10.1016/j.bone.2022.116607openalex-snapshot

Motion grading of high-resolution quantitative computed tomography supported by deep convolutional neural networks

inferred← citeshttps://doi.org/10.1016/j.bspc.2021.102579openalex-snapshot

Deep learning for fast MR imaging: A review for learning reconstruction from incomplete k-space data

inferred← citeshttps://doi.org/10.1016/j.bspc.2022.103598openalex-snapshot

An unsupervised reconstruction method for low-dose CT using deep generative regularization prior

inferred← citeshttps://doi.org/10.1016/j.bspc.2022.104072openalex-snapshot

CT-Net: Cascaded T-shape network using spectral redundancy for dual-energy CT limited-angle reconstruction

inferred← citeshttps://doi.org/10.1016/j.bspc.2023.104868openalex-snapshot

Deep residual constrained reconstruction via learned convolutional sparse coding for low-dose CT imaging

inferred← citeshttps://doi.org/10.1016/j.bspc.2024.106297openalex-snapshot

Artifact suppression for sparse view CT via transformer-based generative adversarial network

inferred← citeshttps://doi.org/10.1016/j.bspc.2024.106793openalex-snapshot

Maternal ECG-guided neural network for improved fetal electrocardiogram extraction

inferred← citeshttps://doi.org/10.1016/j.bspc.2026.109486openalex-snapshot

Elevating MRI reconstruction: A novel enhanced framework integrating deep learning and traditional algorithms for sampling, reconstruction, and training optimization

inferred← citeshttps://doi.org/10.1016/j.bspc.2026.109765openalex-snapshot

Component-wise score diffusion model with momentum-accelerated updates for low-dose CT reconstruction

inferred← citeshttps://doi.org/10.1016/j.bspc.2026.110864openalex-snapshot

Sinogram-based tomography densification and denoising based on a physics-informed deep learning approach

inferred← citeshttps://doi.org/10.1016/j.cam.2021.113973openalex-snapshot

IDPCNN: Iterative denoising and projecting CNN for MRI reconstruction

inferred← citeshttps://doi.org/10.1016/j.cirpj.2024.05.004openalex-snapshot

Machine learning in industrial X-ray computed tomography – a review

inferred← citeshttps://doi.org/10.1016/j.cmpb.2022.107090openalex-snapshot

A cascade of preconditioned conjugate gradient networks for accelerated magnetic resonance imaging

inferred← citeshttps://doi.org/10.1016/j.cmpb.2022.107168openalex-snapshot

A dual-domain neural network based on sinogram synthesis for sparse-view CT reconstruction

inferred← citeshttps://doi.org/10.1016/j.cmpb.2023.107440openalex-snapshot

HFIST-Net: High-throughput fast iterative shrinkage thresholding network for accelerating MR image reconstruction

inferred← citeshttps://doi.org/10.1016/j.cmpb.2024.108010openalex-snapshot

Deep convolutional dictionary learning network for sparse view CT reconstruction with a group sparse prior

inferred← citeshttps://doi.org/10.1016/j.cmpb.2024.108377openalex-snapshot

ATOMMIC: An Advanced Toolbox for Multitask Medical Imaging Consistency to facilitate Artificial Intelligence applications from acquisition to analysis in Magnetic Resonance Imaging

inferred← citeshttps://doi.org/10.1016/j.cmpb.2025.108673openalex-snapshot

Low dose computed tomography reconstruction with momentum-based frequency adjustment network

inferred← citeshttps://doi.org/10.1016/j.commatsci.2021.110356openalex-snapshot

Recurrent localization networks applied to the Lippmann-Schwinger equation

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2022.105710openalex-snapshot

A geometry-informed deep learning framework for ultra-sparse 3D tomographic image reconstruction

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2022.106061openalex-snapshot

DFSNE-Net: Deviant feature sensitive noise estimate network for low-dose CT denoising

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2023.107161openalex-snapshot

CAIR: Combining integrated attention with iterative optimization learning for sparse-view CT reconstruction

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2024.108390openalex-snapshot

RT-SRTS: Angle-agnostic real-time simultaneous 3D reconstruction and tumor segmentation from single X-ray projection

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2025.109853openalex-snapshot

Deep Radon Prior: A fully unsupervised framework for sparse-view CT reconstruction

inferred← citeshttps://doi.org/10.1016/j.compmedimag.2022.102156openalex-snapshot

RISING: A new framework for model-based few-view CT image reconstruction with deep learning

inferred← citeshttps://doi.org/10.1016/j.compmedimag.2024.102345openalex-snapshot

SWISTA-Nets: Subband-adaptive wavelet iterative shrinkage thresholding networks for image reconstruction

inferred← citeshttps://doi.org/10.1016/j.compmedimag.2025.102530openalex-snapshot

Deep Guess acceleration for explainable image reconstruction in sparse-view CT

inferred← citeshttps://doi.org/10.1016/j.displa.2022.102166openalex-snapshot

A model-based deep network for limited-angle computed tomography image reconstruction

inferred← citeshttps://doi.org/10.1016/j.dsp.2020.102856openalex-snapshot

A deep unrolling network inspired by total variation for compressed sensing MRI

inferred← citeshttps://doi.org/10.1016/j.dsp.2022.103734openalex-snapshot

A nonconvex hybrid regularization model for restoring blurred images with mixed noises

inferred← citeshttps://doi.org/10.1016/j.dsp.2023.104058openalex-snapshot

An autoencoder-based model for learning regularizations in unmixing problems

inferred← citeshttps://doi.org/10.1016/j.dsp.2023.104274openalex-snapshot

Efficient physics-based learned reconstruction methods for real-time 3D near-field MIMO radar imaging

inferred← citeshttps://doi.org/10.1016/j.dsp.2025.105235openalex-snapshot

A survey on Deep Image Prior for image denoising

inferred← citeshttps://doi.org/10.1016/j.dsp.2026.106399openalex-snapshot

CPSNet: Physics-inspired label-free deep unfolding for lung ultrasound B-Line detection

inferred← citeshttps://doi.org/10.1016/j.ejmp.2020.11.021openalex-snapshot

Sparse-view CT reconstruction based on multi-level wavelet convolution neural network

inferred← citeshttps://doi.org/10.1016/j.ejmp.2023.102535openalex-snapshot

Deep image and feature prior algorithm based on U-ConformerNet structure

inferred← citeshttps://doi.org/10.1016/j.engappai.2025.112295openalex-snapshot

Sparse view tomographic reconstruction of elongated objects using learned primal-dual networks

inferred← citeshttps://doi.org/10.1016/j.eswa.2025.127703openalex-snapshot

Fast MRI reconstruction: A thorough survey from single-modal to multi-modal

inferred← citeshttps://doi.org/10.1016/j.eswa.2025.130831openalex-snapshot

Test-time reconstruction with physics-integrated dual cooperative learning for unsupervised model adaptation

inferred← citeshttps://doi.org/10.1016/j.image.2022.116763openalex-snapshot

Deep view synthesis with compact and adaptive Multiplane Images

inferred← citeshttps://doi.org/10.1016/j.iopt.2026.100037openalex-snapshot

Physics-informed dual-domain wavelet unrolling for super-resolution imaging in reflective tomography lidar

inferred← citeshttps://doi.org/10.1016/j.jappgeo.2022.104645openalex-snapshot

Deep-learning for accelerating prestack correlative least-squares reverse time migration

inferred← citeshttps://doi.org/10.1016/j.jfranklin.2023.05.023openalex-snapshot

Impulse noise removal by using a nonconvex TGV regularizer and nonconvex fidelity

inferred← citeshttps://doi.org/10.1016/j.jocs.2025.102573openalex-snapshot

Cutting voxel projector a new approach to construct 3D cone beam CT operator

inferred← citeshttps://doi.org/10.1016/j.knosys.2024.111659openalex-snapshot

Image compressed sensing: From deep learning to adaptive learning

inferred← citeshttps://doi.org/10.1016/j.knosys.2025.114060openalex-snapshot

An enhanced deep learning network induced by full visual mechanism for image compressive sensing

inferred← citeshttps://doi.org/10.1016/j.knosys.2026.115832openalex-snapshot

Explicitly provable gradient network for unrolled medical image reconstruction algorithms

inferred← citeshttps://doi.org/10.1016/j.measurement.2025.118121openalex-snapshot

Flex-DD: Deep denoising model with flexible priors for sparse-view CT reconstruction

inferred← citeshttps://doi.org/10.1016/j.media.2019.03.013openalex-snapshot

DeepPET: A deep encoder–decoder network for directly solving the PET image reconstruction inverse problem

showing the first 200 of 760

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