The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is essential for simultaneously improving patient care, accuracy in diagnosis and quality in clinical research. Sponsored by the Royal Society through the Newton Mobility Grant Scheme, a half-day workshop on reconstruction schemes for MR data was held on the 17th of August 2016 to discuss new ideas from related research fields that could be useful to overcome the shortcomings of the conventional reconstruction methods that have been evaluated up to date. Participants were 21 university students, computer scientists, image analysts, engineers and physicists from institutions from 6 different countries. This presentation describes two pipelines for ...
<p>The high-fidelity reconstruction of compressed and lowresolution magnetic resonance (MR) data is ...
Magnetic Resonance Imaging (MRI) offers high-resolution in vivo imaging and rich functional and anat...
This paper addresses the problem of generating a super-resolution (SR) image from a single low-resol...
The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
This thesis presents a new approach to single-image super-resolution (SR), based on sparse signal re...
Sparse coding-based single image super-resolution has attracted much interest. In this paper, a supe...
Single image super-resolution (SR) has been shown useful in Magnetic Resonance (MR) image based diag...
Quality of an image plays a main role in cameras, image enhancement, image reconstruction, and in th...
In this thesis I present a novel approach to superresolution using a network structure. Sparse repre...
The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
Compressed sensing (CS) utilizes the sparsity of MR images to enable accurate reconstruction from un...
In this paper, we introduce a novel fast image reconstruction method for super-resolution (SR) base ...
[EN] The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data ...
Limitations in imaging systems and the effects of changes in sensing have caused limitation in acqui...
<p>The high-fidelity reconstruction of compressed and lowresolution magnetic resonance (MR) data is ...
Magnetic Resonance Imaging (MRI) offers high-resolution in vivo imaging and rich functional and anat...
This paper addresses the problem of generating a super-resolution (SR) image from a single low-resol...
The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
This thesis presents a new approach to single-image super-resolution (SR), based on sparse signal re...
Sparse coding-based single image super-resolution has attracted much interest. In this paper, a supe...
Single image super-resolution (SR) has been shown useful in Magnetic Resonance (MR) image based diag...
Quality of an image plays a main role in cameras, image enhancement, image reconstruction, and in th...
In this thesis I present a novel approach to superresolution using a network structure. Sparse repre...
The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
Compressed sensing (CS) utilizes the sparsity of MR images to enable accurate reconstruction from un...
In this paper, we introduce a novel fast image reconstruction method for super-resolution (SR) base ...
[EN] The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data ...
Limitations in imaging systems and the effects of changes in sensing have caused limitation in acqui...
<p>The high-fidelity reconstruction of compressed and lowresolution magnetic resonance (MR) data is ...
Magnetic Resonance Imaging (MRI) offers high-resolution in vivo imaging and rich functional and anat...
This paper addresses the problem of generating a super-resolution (SR) image from a single low-resol...