An incremental algorithm for non-convex AI-enhanced medical image processing | Paper Citation Record

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This paper cites The gap between theory and practice in function approximation with deep neural networks.

An incremental algorithm for non-convex AI-enhanced medical image processing The gap between theory and practice in function approximation with deep neural networks

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This paper cites Plug-and-play methods for magnetic resonance imaging: Using denoisers for image recovery.

An incremental algorithm for non-convex AI-enhanced medical image processing Plug-and-play methods for magnetic resonance imaging: Using denoisers for image recovery

Reference 2

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This paper cites Solving inverse problems using data- driven models.

An incremental algorithm for non-convex AI-enhanced medical image processing Solving inverse problems using data- driven models

Reference 3

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This paper cites Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward–backward splitting, and regularized gauss–seidel methods.

An incremental algorithm for non-convex AI-enhanced medical image processing Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward–backward splitting, and regularized gauss–seidel methods

Reference 4

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This paper cites The mathematics of adversarial attacks in AI -- Why deep learning is unstable despite the existence of stable neural networks.

An incremental algorithm for non-convex AI-enhanced medical image processing The mathematics of adversarial attacks in AI -- Why deep learning is unstable despite the existence of stable neural networks

Reference 5

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This paper cites Discrete radon transform.

An incremental algorithm for non-convex AI-enhanced medical image processing Discrete radon transform

Reference 6

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This paper cites A new twist: Two-step iterative shrinkage/thresholding algo- rithms for image restoration.

An incremental algorithm for non-convex AI-enhanced medical image processing A new twist: Two-step iterative shrinkage/thresholding algo- rithms for image restoration

Reference 7

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This paper cites A scaled gradient projection method for constrained image deblurring.

An incremental algorithm for non-convex AI-enhanced medical image processing A scaled gradient projection method for constrained image deblurring

Reference 8

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This paper cites Iterated hard shrinkage for minimization problems with sparsity constraints.

An incremental algorithm for non-convex AI-enhanced medical image processing Iterated hard shrinkage for minimization problems with sparsity constraints

Reference 9

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This paper cites Bubba, Luca Calatroni, Ambra Catozzi, Serena Crisci, Thomas Pock, Monica Pragliola, Siiri Rautio, Danilo Riccio, and Andrea Sebastiani.

An incremental algorithm for non-convex AI-enhanced medical image processing Bubba, Luca Calatroni, Ambra Catozzi, Serena Crisci, Thomas Pock, Monica Pragliola, Siiri Rautio, Danilo Riccio, and Andrea Sebastiani

Reference 10

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This paper cites Learning the invisible: A hybrid deep learning-shearlet framework for limited angle computed tomography.

An incremental algorithm for non-convex AI-enhanced medical image processing Learning the invisible: A hybrid deep learning-shearlet framework for limited angle computed tomography

Reference 11

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This paper cites Bilevel approaches for learning of variational imaging models.Variational Methods: In Imaging and Geometric Control, 18(252):2, 2017.

An incremental algorithm for non-convex AI-enhanced medical image processing Bilevel approaches for learning of variational imaging models.Variational Methods: In Imaging and Geometric Control, 18(252):2, 2017

Reference 12

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This paper cites Enhancing sparsity by reweighted L1 minimization.

An incremental algorithm for non-convex AI-enhanced medical image processing Enhancing sparsity by reweighted L1 minimization

Reference 13

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This paper cites Plug-and-play gradient- based denoisers applied to ct image enhancement.

An incremental algorithm for non-convex AI-enhanced medical image processing Plug-and-play gradient- based denoisers applied to ct image enhancement

Reference 14

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This paper cites Gpu acceleration of a model-based iterative method for digital breast tomosynthesis.

An incremental algorithm for non-convex AI-enhanced medical image processing Gpu acceleration of a model-based iterative method for digital breast tomosynthesis

Reference 15

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This paper cites A first-order primal-dual algorithm for convex problems with applications to imaging.

An incremental algorithm for non-convex AI-enhanced medical image processing A first-order primal-dual algorithm for convex problems with applications to imaging

Reference 16

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This paper cites Exact reconstruction of sparse signals via nonconvex minimization.

An incremental algorithm for non-convex AI-enhanced medical image processing Exact reconstruction of sparse signals via nonconvex minimization

Reference 17

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This paper cites Fast algorithms for nonconvex compressive sensing: Mri reconstruction from very few data.

An incremental algorithm for non-convex AI-enhanced medical image processing Fast algorithms for nonconvex compressive sensing: Mri reconstruction from very few data

Reference 18

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This paper cites Iteratively reweighted least squares minimization for sparse recovery.

An incremental algorithm for non-convex AI-enhanced medical image processing Iteratively reweighted least squares minimization for sparse recovery

Reference 19

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This paper cites To be or not to be stable, that is the question: understanding neural networks for inverse problems.

An incremental algorithm for non-convex AI-enhanced medical image processing To be or not to be stable, that is the question: understanding neural networks for inverse problems

Reference 20

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

An incremental algorithm for non-convex AI-enhanced medical image processing RISING: A new framework for model- based few-view CT image reconstruction with deep learning

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This paper cites Ambiguity in solving imaging inverse problems with deep-learning-based operators.

An incremental algorithm for non-convex AI-enhanced medical image processing Ambiguity in solving imaging inverse problems with deep-learning-based operators

Reference 22

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This paper cites Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems.

An incremental algorithm for non-convex AI-enhanced medical image processing Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems

Reference 23

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This paper cites Solving inverse problems with deep neural networks- robustness included.

An incremental algorithm for non-convex AI-enhanced medical image processing Solving inverse problems with deep neural networks- robustness included

Reference 24

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This paper cites Deep Residual Learning for Compressed Sensing CT Reconstruction via Persistent Homology Analysis.

An incremental algorithm for non-convex AI-enhanced medical image processing Deep Residual Learning for Compressed Sensing CT Reconstruction via Persistent Homology Analysis

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This paper cites Framing u-net via deep convolutional framelets: Application to sparse-view ct.

An incremental algorithm for non-convex AI-enhanced medical image processing Framing u-net via deep convolutional framelets: Application to sparse-view ct

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This paper cites Deep learning-based solvability of underdetermined inverse problems in medical imaging.Medical Image Analysis, 69:101967, 2021.

An incremental algorithm for non-convex AI-enhanced medical image processing Deep learning-based solvability of underdetermined inverse problems in medical imaging.Medical Image Analysis, 69:101967, 2021

Reference 27

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This paper cites Resunet++: An advanced architecture for medical image segmentation.

An incremental algorithm for non-convex AI-enhanced medical image processing Resunet++: An advanced architecture for medical image segmentation

Reference 28

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This paper cites Plug-and-play methods for integrating physical and learned models in computational imaging: Theory, algorithms, and applications.

An incremental algorithm for non-convex AI-enhanced medical image processing Plug-and-play methods for integrating physical and learned models in computational imaging: Theory, algorithms, and applications

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This paper cites Learning regularization parameter-maps for variational image reconstruction using deep neural networks and algorithm unrolling.

An incremental algorithm for non-convex AI-enhanced medical image processing Learning regularization parameter-maps for variational image reconstruction using deep neural networks and algorithm unrolling

Reference 30

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This paper cites Brain tumor segmentation of the flair mri images using novel resunet.

An incremental algorithm for non-convex AI-enhanced medical image processing Brain tumor segmentation of the flair mri images using novel resunet

Reference 31

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This paper cites On gradients of functions definable in o-minimal structures.

An incremental algorithm for non-convex AI-enhanced medical image processing On gradients of functions definable in o-minimal structures

Reference 32

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This paper cites A nonconvex penalization algorithm with automatic choice of the regularization parameter in sparse imaging.

An incremental algorithm for non-convex AI-enhanced medical image processing A nonconvex penalization algorithm with automatic choice of the regularization parameter in sparse imaging

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This paper cites A fast total variation-based iterative algorithm for digital breast tomosynthesis image reconstruction.

An incremental algorithm for non-convex AI-enhanced medical image processing A fast total variation-based iterative algorithm for digital breast tomosynthesis image reconstruction

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This paper cites Deep guess acceleration for explainable image reconstruction in sparse-view ct.

An incremental algorithm for non-convex AI-enhanced medical image processing Deep guess acceleration for explainable image reconstruction in sparse-view ct

Reference 35

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This paper cites A model-based optimization framework for iterative digital breast tomosynthesis image reconstruction.

An incremental algorithm for non-convex AI-enhanced medical image processing A model-based optimization framework for iterative digital breast tomosynthesis image reconstruction

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This paper cites Tu-fg-207a-04: Overview of the Low Dose CT Grand Challenge.

An incremental algorithm for non-convex AI-enhanced medical image processing Tu-fg-207a-04: Overview of the Low Dose CT Grand Challenge

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This paper cites Sparse Recovery using Smoothed $\ell^0$ (SL0): Convergence Analysis.

An incremental algorithm for non-convex AI-enhanced medical image processing Sparse Recovery using Smoothed $\ell^0$ (SL0): Convergence Analysis

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This paper cites A fast approach for overcomplete sparse de- composition based on smoothed\ell 0 norm.

An incremental algorithm for non-convex AI-enhanced medical image processing A fast approach for overcomplete sparse de- composition based on smoothed\ell 0 norm

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This paper cites Algorithm unrolling: Interpretable, efficient deep learning for signal and image processing.

An incremental algorithm for non-convex AI-enhanced medical image processing Algorithm unrolling: Interpretable, efficient deep learning for signal and image processing

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This paper cites An iterative l{1}-based image restoration algorithm with an adap- tive parameter estimation.

An incremental algorithm for non-convex AI-enhanced medical image processing An iterative l{1}-based image restoration algorithm with an adap- tive parameter estimation

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This paper cites Fast sparse image reconstruction using adaptive nonlinear filtering.

An incremental algorithm for non-convex AI-enhanced medical image processing Fast sparse image reconstruction using adaptive nonlinear filtering

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This paper cites A fast algorithm for nonconvex approaches to sparse recovery problems.

An incremental algorithm for non-convex AI-enhanced medical image processing A fast algorithm for nonconvex approaches to sparse recovery problems

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This paper cites A green prospective for learned post-processing in sparse-view tomographic reconstruction.

An incremental algorithm for non-convex AI-enhanced medical image processing A green prospective for learned post-processing in sparse-view tomographic reconstruction

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Observation e7244c52-7498-47c1-9e2d-8e96d928bc93 · outbound

This paper cites Robust non-convex model-based approach for deep learning-based image processing.

An incremental algorithm for non-convex AI-enhanced medical image processing Robust non-convex model-based approach for deep learning-based image processing

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This paper cites Minimizing nonconvex functions for sparse vector reconstruction.

An incremental algorithm for non-convex AI-enhanced medical image processing Minimizing nonconvex functions for sparse vector reconstruction

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Observation 186404b1-124b-4367-96bf-10164e1d7593 · outbound

This paper cites On iteratively reweighted algorithms for nonsmooth nonconvex optimization in computer vision.

An incremental algorithm for non-convex AI-enhanced medical image processing On iteratively reweighted algorithms for nonsmooth nonconvex optimization in computer vision

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Observation ccbf49e4-804c-41e6-8e5b-8ab6a5049821 · outbound

This paper cites Why do commercial ct scanners still employ traditional, filtered back-projection for image reconstruction? Inverse problems, 25(12):123009, 2009.

An incremental algorithm for non-convex AI-enhanced medical image processing Why do commercial ct scanners still employ traditional, filtered back-projection for image reconstruction? Inverse problems, 25(12):123009, 2009

Reference 48

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This paper cites U-net: Convolutional networks for biomedical image seg- mentation.

An incremental algorithm for non-convex AI-enhanced medical image processing U-net: Convolutional networks for biomedical image seg- mentation

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This paper cites Sidky and et al.

An incremental algorithm for non-convex AI-enhanced medical image processing Sidky and et al

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Observation 91e1d145-497a-41b6-b680-4b17217029da · outbound

This paper cites Sidky and et al.

An incremental algorithm for non-convex AI-enhanced medical image processing Sidky and et al

Reference 51

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

An incremental algorithm for non-convex AI-enhanced medical image processing Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle–Pock algorithm

Reference 52

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This paper cites Relaxed conditions for sparse signal recovery with general concave priors.

An incremental algorithm for non-convex AI-enhanced medical image processing Relaxed conditions for sparse signal recovery with general concave priors

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:03:01.782541Z

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Observation 64fc1be4-918a-455f-ae31-9d43fa5432a4 · outbound

This paper cites Fast and flexible x-ray tomography using the astra toolbox.

An incremental algorithm for non-convex AI-enhanced medical image processing Fast and flexible x-ray tomography using the astra toolbox

Reference 54

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This paper cites The astra toolbox: A platform for advanced algorithm development in electron tomography.

An incremental algorithm for non-convex AI-enhanced medical image processing The astra toolbox: A platform for advanced algorithm development in electron tomography

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:03:01.754836Z

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Observation 0fa5569a-6f3e-4e63-b8ac-9c3be415d78a · outbound

This paper cites Plug-and-play priors for model based reconstruction.

An incremental algorithm for non-convex AI-enhanced medical image processing Plug-and-play priors for model based reconstruction

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:03:01.737188Z

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Observation 536a722f-a1bf-48af-90c0-286b26a08e61 · outbound

This paper cites A deep residual architecture for skin lesion segmentation.

An incremental algorithm for non-convex AI-enhanced medical image processing A deep residual architecture for skin lesion segmentation

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:03:01.717267Z

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Observation 82fef48e-9795-4fca-a360-072a12be682b · outbound

This paper cites Admm-based deep reconstruction for limited-angle ct.

An incremental algorithm for non-convex AI-enhanced medical image processing Admm-based deep reconstruction for limited-angle ct

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:03:01.699798Z

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Observation dd250bf4-f8a0-470e-982d-9140876d587d · outbound

This paper cites Multiscale structural similarity for image quality assessment.

An incremental algorithm for non-convex AI-enhanced medical image processing Multiscale structural similarity for image quality assessment

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:03:01.682420Z

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Observation 0762c9bb-a486-44c6-b03f-39a39dc469b5 · outbound

This paper cites Iterative reweighted\ell 1 and\ell 2 methods for finding sparse solutions.

An incremental algorithm for non-convex AI-enhanced medical image processing Iterative reweighted\ell 1 and\ell 2 methods for finding sparse solutions

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:03:01.647813Z

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Observation 7f7a348a-b69f-445e-a34a-e705f58d39d5 · outbound

This paper cites Deep convolutional framelets: A general deep learning framework for inverse problems.

An incremental algorithm for non-convex AI-enhanced medical image processing Deep convolutional framelets: A general deep learning framework for inverse problems

Reference 61

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Observation 269f3abb-6b57-40b2-9479-f5b455973719 · outbound

This paper cites Domain Generalization for Medical Image Analysis: A Review.

An incremental algorithm for non-convex AI-enhanced medical image processing Domain Generalization for Medical Image Analysis: A Review

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-15T22:03:01.441313Z

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Observation 8ee11c31-210c-4df0-93ba-1132342fa28c · outbound

This paper cites Low-dose ct via deep cnn with skip connection and network-in-network.

An incremental algorithm for non-convex AI-enhanced medical image processing Low-dose ct via deep cnn with skip connection and network-in-network

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:03:01.619864Z

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Observation 0cd8a929-b4da-407c-984f-3324dbf039cc · outbound

This paper cites Road extraction by deep residual u-net.

An incremental algorithm for non-convex AI-enhanced medical image processing Road extraction by deep residual u-net

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-15T22:03:01.451566Z

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Observation b5cac84f-86c8-4013-9579-6d4d9e290b21 · outbound

This paper cites Hybrid skip: A biologically inspired skip connection for the unet architecture.

An incremental algorithm for non-convex AI-enhanced medical image processing Hybrid skip: A biologically inspired skip connection for the unet architecture

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:03:01.593600Z

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Observation a739387c-f101-443f-9868-bb8e9b0a60a2 · outbound

This paper cites Fondo per il Programma Nazionale di Ricerca e Progetti di Rilevante Inter- esse Nazionale (PRIN).

An incremental algorithm for non-convex AI-enhanced medical image processing Fondo per il Programma Nazionale di Ricerca e Progetti di Rilevante Inter- esse Nazionale (PRIN)

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:03:01.577395Z

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Observation 9508c1af-c852-4e8a-b55b-e1c026e750b7 · outbound

This paper cites 21 A PREPRINT - MAY 14, 2025.

An incremental algorithm for non-convex AI-enhanced medical image processing 21 A PREPRINT - MAY 14, 2025

Reference 1402

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:03:01.665416Z

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