Medical image synthesis with deep convolutional adversarial networks
Medical imaging plays a critical role in various clinical applications. However, due to
multiple considerations such as cost and radiation dose, the acquisition of certain image …
multiple considerations such as cost and radiation dose, the acquisition of certain image …
Multiscale brain MRI super-resolution using deep 3D convolutional networks
CH Pham, C Tor-Díez, H Meunier, N Bednarek… - … Medical Imaging and …, 2019 - Elsevier
The purpose of super-resolution approaches is to overcome the hardware limitations and
the clinical requirements of imaging procedures by reconstructing high-resolution images …
the clinical requirements of imaging procedures by reconstructing high-resolution images …
Multi-contrast super-resolution MRI through a progressive network
Magnetic resonance imaging (MRI) is widely used for screening, diagnosis, image-guided
therapy, and scientific research. A significant advantage of MRI over other imaging …
therapy, and scientific research. A significant advantage of MRI over other imaging …
Magnetic resonance image reconstruction from undersampled measurements using a patch-based nonlocal operator
Abstract Compressed sensing MRI (CS-MRI) has shown great potential in reducing data
acquisition time in MRI. Sparsity or compressibility plays an important role to reduce the …
acquisition time in MRI. Sparsity or compressibility plays an important role to reduce the …
Channel splitting network for single MR image super-resolution
High resolution magnetic resonance (MR) imaging is desirable in many clinical applications
due to its contribution to more accurate subsequent analyses and early clinical diagnoses …
due to its contribution to more accurate subsequent analyses and early clinical diagnoses …
Simultaneous single-and multi-contrast super-resolution for brain MRI images based on a convolutional neural network
In magnetic resonance imaging (MRI), the acquired images are usually not of high enough
resolution due to constraints such as long sampling times and patient comfort. High …
resolution due to constraints such as long sampling times and patient comfort. High …
Synthesized 7T MRI from 3T MRI via deep learning in spatial and wavelet domains
Ultra-high field 7T MRI scanners, while producing images with exceptional anatomical
details, are cost prohibitive and hence highly inaccessible. In this paper, we introduce a …
details, are cost prohibitive and hence highly inaccessible. In this paper, we introduce a …
Single-image super-resolution of brain MR images using overcomplete dictionaries
Resolution in Magnetic Resonance (MR) is limited by diverse physical, technological and
economical considerations. In conventional medical practice, resolution enhancement is …
economical considerations. In conventional medical practice, resolution enhancement is …
[HTML][HTML] Super-resolution of cardiac MR cine imaging using conditional GANs and unsupervised transfer learning
Y Xia, N Ravikumar, JP Greenwood, S Neubauer… - Medical Image …, 2021 - Elsevier
Abstract High-resolution (HR), isotropic cardiac Magnetic Resonance (MR) cine imaging is
challenging since it requires long acquisition and patient breath-hold times. Instead, 2D …
challenging since it requires long acquisition and patient breath-hold times. Instead, 2D …
Robust skull stripping using multiple MR image contrasts insensitive to pathology
Automatic skull-stripping or brain extraction of magnetic resonance (MR) images is often a
fundamental step in many neuroimage processing pipelines. The accuracy of subsequent …
fundamental step in many neuroimage processing pipelines. The accuracy of subsequent …