A review on deep learning in medical image reconstruction
Medical imaging is crucial in modern clinics to provide guidance to the diagnosis and
treatment of diseases. Medical image reconstruction is one of the most fundamental and …
treatment of diseases. Medical image reconstruction is one of the most fundamental and …
[BOOK][B] Foundations of time-frequency analysis
K Gröchenig - 2013 - books.google.com
Time-frequency analysis is a modern branch of harmonic analysis. It com prises all those
parts of mathematics and its applications that use the struc ture of translations and …
parts of mathematics and its applications that use the struc ture of translations and …
Sparse microwave imaging: Principles and applications
BC Zhang, W Hong, YR Wu - Science China Information Sciences, 2012 - Springer
This paper provides principles and applications of the sparse microwave imaging theory and
technology. Synthetic aperture radar (SAR) is an important method of modern remote …
technology. Synthetic aperture radar (SAR) is an important method of modern remote …
Compressed sensing with coherent and redundant dictionaries
This article presents novel results concerning the recovery of signals from undersampled
data in the common situation where such signals are not sparse in an orthonormal basis or …
data in the common situation where such signals are not sparse in an orthonormal basis or …
Framelets: MRA-based constructions of wavelet frames
We discuss wavelet frames constructed via multiresolution analysis (MRA), with emphasis
on tight wavelet frames. In particular, we establish general principles and specific algorithms …
on tight wavelet frames. In particular, we establish general principles and specific algorithms …
Split Bregman methods and frame based image restoration
Split Bregman methods introduced in [T. Goldstein and S. Osher, SIAM J. Imaging Sci., 2
(2009), pp. 323–343] have been demonstrated to be efficient tools for solving total variation …
(2009), pp. 323–343] have been demonstrated to be efficient tools for solving total variation …
[BOOK][B] Frames and bases: An introductory course
O Christensen - 2008 - books.google.com
During the last several years, frames have become increasingly popular; they have
appeared in a large number of applications, and several concrete constructions of frames of …
appeared in a large number of applications, and several concrete constructions of frames of …
Framelet representation of tensor nuclear norm for third-order tensor completion
The main aim of this paper is to develop a framelet representation of the tensor nuclear norm
for third-order tensor recovery. In the literature, the tensor nuclear norm can be computed by …
for third-order tensor recovery. In the literature, the tensor nuclear norm can be computed by …
Image restoration: total variation, wavelet frames, and beyond
The variational techniques (eg the total variation based method) are well established and
effective for image restoration, as well as many other applications, while the wavelet frame …
effective for image restoration, as well as many other applications, while the wavelet frame …
Deep learning via dynamical systems: An approximation perspective
We build on the dynamical systems approach to deep learning, where deep residual
networks are idealized as continuous-time dynamical systems, from the approximation …
networks are idealized as continuous-time dynamical systems, from the approximation …