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Learning The Invisible: A Hybrid Deep Learning-Shearlet Framework for
  Limited Angle Computed Tomography

Learning The Invisible: A Hybrid Deep Learning-Shearlet Framework for Limited Angle Computed Tomography

12 November 2018
T. Bubba
Gitta Kutyniok
Matti Lassas
M. März
Wojciech Samek
S. Siltanen
Vignesh Srinivasan
ArXivPDFHTML

Papers citing "Learning The Invisible: A Hybrid Deep Learning-Shearlet Framework for Limited Angle Computed Tomography"

44 / 44 papers shown
Title
An incremental algorithm for non-convex AI-enhanced medical image processing
An incremental algorithm for non-convex AI-enhanced medical image processing
Elena Morotti
34
0
0
13 May 2025
Iterative CT Reconstruction via Latent Variable Optimization of Shallow
  Diffusion Models
Iterative CT Reconstruction via Latent Variable Optimization of Shallow Diffusion Models
S. Ozaki
S. Kaji
T. Imae
K. Nawa
H. Yamashita
K. Nakagawa
DiffM
MedIm
32
0
0
06 Aug 2024
Space-Variant Total Variation boosted by learning techniques in few-view
  tomographic imaging
Space-Variant Total Variation boosted by learning techniques in few-view tomographic imaging
E. Morotti
Davide Evangelista
Andrea Sebastiani
E. L. Piccolomini
41
1
0
25 Apr 2024
Mathematical Algorithm Design for Deep Learning under Societal and
  Judicial Constraints: The Algorithmic Transparency Requirement
Mathematical Algorithm Design for Deep Learning under Societal and Judicial Constraints: The Algorithmic Transparency Requirement
Holger Boche
Adalbert Fono
Gitta Kutyniok
FaML
25
4
0
18 Jan 2024
Learned reconstruction methods for inverse problems: sample error
  estimates
Learned reconstruction methods for inverse problems: sample error estimates
Luca Ratti
24
0
0
21 Dec 2023
Meta-Prior: Meta learning for Adaptive Inverse Problem Solvers
Meta-Prior: Meta learning for Adaptive Inverse Problem Solvers
M. Terris
Thomas Moreau
24
0
0
30 Nov 2023
Limited-Angle Tomography Reconstruction via Deep End-To-End Learning on
  Synthetic Data
Limited-Angle Tomography Reconstruction via Deep End-To-End Learning on Synthetic Data
Thomas Germer
Jan Robine
S. Konietzny
Stefan Harmeling
Tobias Uelwer
MedIm
16
5
0
13 Sep 2023
Transgressing the boundaries: towards a rigorous understanding of deep
  learning and its (non-)robustness
Transgressing the boundaries: towards a rigorous understanding of deep learning and its (non-)robustness
C. Hartmann
Lorenz Richter
AAML
16
2
0
05 Jul 2023
Stretched sinograms for limited-angle tomographic reconstruction with
  neural networks
Stretched sinograms for limited-angle tomographic reconstruction with neural networks
Kyle L. Luther
Sebastian Seung
16
0
0
16 Jun 2023
Data Models for Dataset Drift Controls in Machine Learning With Optical
  Images
Data Models for Dataset Drift Controls in Machine Learning With Optical Images
Luis Oala
Marco Aversa
Gabriel Nobis
Kurt Willis
Yoan Neuenschwander
...
E. Pomarico
Wojciech Samek
Roderick Murray-Smith
Christoph Clausen
B. Sanguinetti
23
5
0
04 Nov 2022
Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis
Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis
Luca Galimberti
Anastasis Kratsios
Giulia Livieri
OOD
28
14
0
24 Oct 2022
Continuous approximation by convolutional neural networks with a
  sigmoidal function
Continuous approximation by convolutional neural networks with a sigmoidal function
Weike Chang
18
0
0
27 Sep 2022
LRIP-Net: Low-Resolution Image Prior based Network for Limited-Angle CT
  Reconstruction
LRIP-Net: Low-Resolution Image Prior based Network for Limited-Angle CT Reconstruction
Qifeng Gao
Rui Ding
Linyuan Wang
Bin Xue
Y. Duan
9
5
0
30 Jul 2022
Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning
Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning
Martin Genzel
Ingo Gühring
Jan Macdonald
M. März
25
25
0
14 Jun 2022
On Learning the Invisible in Photoacoustic Tomography with Flat
  Directionally Sensitive Detector
On Learning the Invisible in Photoacoustic Tomography with Flat Directionally Sensitive Detector
Bolin Pan
M. Betcke
13
2
0
21 Apr 2022
Physics-assisted Generative Adversarial Network for X-Ray Tomography
Physics-assisted Generative Adversarial Network for X-Ray Tomography
Zhen Guo
J. Song
George Barbastathis
M. Glinsky
C. Vaughan
K. Larson
B. Alpert
Z. Levine
GAN
MedIm
14
9
0
07 Apr 2022
Limitations of Deep Learning for Inverse Problems on Digital Hardware
Limitations of Deep Learning for Inverse Problems on Digital Hardware
Holger Boche
Adalbert Fono
Gitta Kutyniok
24
25
0
28 Feb 2022
Training Adaptive Reconstruction Networks for Blind Inverse Problems
Training Adaptive Reconstruction Networks for Blind Inverse Problems
Alban Gossard
P. Weiss
MedIm
24
5
0
23 Feb 2022
Advantage of Machine Learning over Maximum Likelihood in Limited-Angle
  Low-Photon X-Ray Tomography
Advantage of Machine Learning over Maximum Likelihood in Limited-Angle Low-Photon X-Ray Tomography
Zhen Guo
J. Song
George Barbastathis
M. Glinsky
C. Vaughan
K. Larson
B. Alpert
Z. Levine
20
1
0
15 Nov 2021
Efficient Hierarchical Bayesian Inference for Spatio-temporal Regression
  Models in Neuroimaging
Efficient Hierarchical Bayesian Inference for Spatio-temporal Regression Models in Neuroimaging
Ali Hashemi
Yijing Gao
Chang Cai
Sanjay Ghosh
Klaus-Robert Muller
S. Nagarajan
Stefan Haufe
21
7
0
02 Nov 2021
WARPd: A linearly convergent first-order method for inverse problems
  with approximate sharpness conditions
WARPd: A linearly convergent first-order method for inverse problems with approximate sharpness conditions
Matthew J. Colbrook
21
2
0
24 Oct 2021
Deep Microlocal Reconstruction for Limited-Angle Tomography
Deep Microlocal Reconstruction for Limited-Angle Tomography
Héctor Andrade-Loarca
Gitta Kutyniok
Ozan Oktem
P. Petersen
20
8
0
12 Aug 2021
AAPM DL-Sparse-View CT Challenge Submission Report: Designing an
  Iterative Network for Fanbeam-CT with Unknown Geometry
AAPM DL-Sparse-View CT Challenge Submission Report: Designing an Iterative Network for Fanbeam-CT with Unknown Geometry
Martin Genzel
Jan Macdonald
M. März
8
4
0
01 Jun 2021
Can stable and accurate neural networks be computed? -- On the barriers
  of deep learning and Smale's 18th problem
Can stable and accurate neural networks be computed? -- On the barriers of deep learning and Smale's 18th problem
Matthew J. Colbrook
Vegard Antun
A. Hansen
67
129
0
20 Jan 2021
Parallel-beam X-ray CT datasets of apples with internal defects and
  label balancing for machine learning
Parallel-beam X-ray CT datasets of apples with internal defects and label balancing for machine learning
S. Coban
Vladyslav Andriiashen
P. Ganguly
Maureen van Eijnatten
K. Batenburg
11
2
0
24 Dec 2020
Solving Inverse Problems With Deep Neural Networks -- Robustness
  Included?
Solving Inverse Problems With Deep Neural Networks -- Robustness Included?
Martin Genzel
Jan Macdonald
M. März
AAML
OOD
19
101
0
09 Nov 2020
TorchRadon: Fast Differentiable Routines for Computed Tomography
TorchRadon: Fast Differentiable Routines for Computed Tomography
Matteo Ronchetti
OOD
MedIm
20
63
0
29 Sep 2020
Data and Image Prior Integration for Image Reconstruction Using
  Consensus Equilibrium
Data and Image Prior Integration for Image Reconstruction Using Consensus Equilibrium
Student Member Ieee Muhammad Usman Ghani
F. I. W. Clem Karl
13
16
0
31 Aug 2020
Langevin Cooling for Domain Translation
Langevin Cooling for Domain Translation
Vignesh Srinivasan
Klaus-Robert Muller
Wojciech Samek
Shinichi Nakajima
36
1
0
31 Aug 2020
A model-guided deep network for limited-angle computed tomography
A model-guided deep network for limited-angle computed tomography
Wei Wang
X. Xia
Chuanjiang He
Zemin Ren
Jian Lu
Tianfu Wang
Baiying Lei
3DV
MedIm
11
0
0
10 Aug 2020
A deep primal-dual proximal network for image restoration
A deep primal-dual proximal network for image restoration
Mingyuan Jiu
N. Pustelnik
16
21
0
02 Jul 2020
Learning the geometry of wave-based imaging
Learning the geometry of wave-based imaging
K. Kothari
Maarten V. de Hoop
Ivan Dokmanić
AI4CE
11
8
0
10 Jun 2020
Regularization of Inverse Problems by Neural Networks
Regularization of Inverse Problems by Neural Networks
Markus Haltmeier
Linh V. Nguyen
14
18
0
06 Jun 2020
Deep neural networks for inverse problems with pseudodifferential
  operators: an application to limited-angle tomography
Deep neural networks for inverse problems with pseudodifferential operators: an application to limited-angle tomography
T. Bubba
Mathilde Galinier
Matti Lassas
M. Prato
Luca Ratti
S. Siltanen
6
29
0
02 Jun 2020
On Learned Operator Correction in Inverse Problems
On Learned Operator Correction in Inverse Problems
Sebastian Lunz
A. Hauptmann
T. Tarvainen
Carola-Bibiane Schönlieb
Simon Arridge
4
3
0
14 May 2020
Interval Neural Networks as Instability Detectors for Image
  Reconstructions
Interval Neural Networks as Instability Detectors for Image Reconstructions
Jan Macdonald
M. März
Luis Oala
Wojciech Samek
12
2
0
27 Mar 2020
Interval Neural Networks: Uncertainty Scores
Interval Neural Networks: Uncertainty Scores
Luis Oala
Cosmas Heiß
Jan Macdonald
M. März
Wojciech Samek
Gitta Kutyniok
UQCV
10
25
0
25 Mar 2020
Computed Tomography Reconstruction Using Deep Image Prior and Learned
  Reconstruction Methods
Computed Tomography Reconstruction Using Deep Image Prior and Learned Reconstruction Methods
Daniel Otero Baguer
Johannes Leuschner
Maximilian Schmidt
21
185
0
10 Mar 2020
Integrating Scientific Knowledge with Machine Learning for Engineering
  and Environmental Systems
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems
J. Willard
X. Jia
Shaoming Xu
M. Steinbach
Vipin Kumar
AI4CE
88
387
0
10 Mar 2020
Limited Angle Tomography for Transmission X-Ray Microscopy Using Deep
  Learning
Limited Angle Tomography for Transmission X-Ray Microscopy Using Deep Learning
Yixing Huang
Shengxiang Wang
Y. Guan
Andreas K. Maier
MedIm
9
23
0
08 Jan 2020
Deep learning architectures for nonlinear operator functions and
  nonlinear inverse problems
Deep learning architectures for nonlinear operator functions and nonlinear inverse problems
Maarten V. de Hoop
Matti Lassas
C. Wong
17
25
0
23 Dec 2019
Data Consistent Artifact Reduction for Limited Angle Tomography with
  Deep Learning Prior
Data Consistent Artifact Reduction for Limited Angle Tomography with Deep Learning Prior
Yixing Huang
Alexander Preuhs
G. Lauritsch
M. Manhart
Xiaolin Huang
Andreas K. Maier
6
38
0
19 Aug 2019
Approximation spaces of deep neural networks
Approximation spaces of deep neural networks
Rémi Gribonval
Gitta Kutyniok
M. Nielsen
Felix Voigtländer
8
124
0
03 May 2019
Extraction of digital wavefront sets using applied harmonic analysis and
  deep neural networks
Extraction of digital wavefront sets using applied harmonic analysis and deep neural networks
Héctor Andrade-Loarca
Gitta Kutyniok
Ozan Oktem
P. Petersen
22
15
0
05 Jan 2019
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