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Deep Variational Networks with Exponential Weighting for Learning Computed Tomography

Deep Variational Networks with Exponential Weighting for Learning Computed Tomography

V. Vishnevskiy
R. Rau
O. Goksel
ArXiv (abs)PDFHTML

Papers citing "Deep Variational Networks with Exponential Weighting for Learning Computed Tomography"

6 / 6 papers shown
Title
OADAT: Experimental and Synthetic Clinical Optoacoustic Data for Standardized Image Processing
OADAT: Experimental and Synthetic Clinical Optoacoustic Data for Standardized Image Processing
Firat Ozdemir
Berkan Lafci
X. L. Deán-Ben
D. Razansky
Fernando Perez-Cruz
22
5
0
17 Jun 2022
Learned Cone-Beam CT Reconstruction Using Neural Ordinary Differential Equations
Learned Cone-Beam CT Reconstruction Using Neural Ordinary Differential Equations
Mareike Thies
Fabian Wagner
Mingxuan Gu
Lukas Folle
Lina Felsner
Andreas Maier
32
4
0
19 Jan 2022
Training Variational Networks with Multi-Domain Simulations: Speed-of-Sound Image Reconstruction
Training Variational Networks with Multi-Domain Simulations: Speed-of-Sound Image Reconstruction
Mélanie Bernhardt
V. Vishnevskiy
R. Rau
O. Goksel
OOD
54
23
0
25 Jun 2020
Deep Network for Scatterer Distribution Estimation for Ultrasound Image Simulation
Deep Network for Scatterer Distribution Estimation for Ultrasound Image Simulation
Lin Zhang
V. Vishnevskiy
O. Goksel
OOD
67
15
0
17 Jun 2020
Data Consistent CT Reconstruction from Insufficient Data with Learned Prior Images
Data Consistent CT Reconstruction from Insufficient Data with Learned Prior Images
Yixing Huang
Alexander Preuhs
M. Manhart
G. Lauritsch
Andreas Maier
MedIm
153
5
0
20 May 2020
Deep variational network for rapid 4D flow MRI reconstruction
Deep variational network for rapid 4D flow MRI reconstruction
V. Vishnevskiy
Jonas Walheim
Sebastian Kozerke
61
69
0
20 Apr 2020