Cardiac MRI: state of the art
Cardiac MRI plays an important role in the evaluation of cardiovascular diseases (CVDs),
including ischemic heart disease, cardiomyopathy, valvular disease, congenital disease …
including ischemic heart disease, cardiomyopathy, valvular disease, congenital disease …
Deep learning in photoacoustic tomography: current approaches and future directions
A Hauptmann, B Cox - Journal of Biomedical Optics, 2020 - spiedigitallibrary.org
Biomedical photoacoustic tomography, which can provide high-resolution 3D soft tissue
images based on optical absorption, has advanced to the stage at which translation from the …
images based on optical absorption, has advanced to the stage at which translation from the …
Unsupervised MRI reconstruction via zero-shot learned adversarial transformers
Supervised reconstruction models are characteristically trained on matched pairs of
undersampled and fully-sampled data to capture an MRI prior, along with supervision …
undersampled and fully-sampled data to capture an MRI prior, along with supervision …
Deep magnetic resonance image reconstruction: Inverse problems meet neural networks
Image reconstruction from undersampled k-space data has been playing an important role
in fast magnetic resonance imaging (MRI). Recently, deep learning has demonstrated …
in fast magnetic resonance imaging (MRI). Recently, deep learning has demonstrated …
Accelerate gas diffusion-weighted MRI for lung morphometry with deep learning
C Duan, H Deng, S Xiao, J Xie, H Li, X Zhao, D Han… - European …, 2022 - Springer
Objectives Multiple b-value gas diffusion-weighted MRI (DW-MRI) enables non-invasive and
quantitative assessment of lung morphometry, but its long acquisition time is not well …
quantitative assessment of lung morphometry, but its long acquisition time is not well …
Plug-and-play methods for magnetic resonance imaging: Using denoisers for image recovery
Magnetic resonance imaging (MRI) is a noninvasive diagnostic tool that provides excellent
soft-tissue contrast without the use of ionizing radiation. Compared to other clinical imaging …
soft-tissue contrast without the use of ionizing radiation. Compared to other clinical imaging …
Improvement of image quality at CT and MRI using deep learning
Deep learning has been developed by computer scientists. Here, we discuss techniques for
improving the image quality of diagnostic computed tomography and magnetic resonance …
improving the image quality of diagnostic computed tomography and magnetic resonance …
A novel hybrid approach based on deep cnn features to detect knee osteoarthritis
In the recent era, various diseases have severely affected the lifestyle of individuals,
especially adults. Among these, bone diseases, including Knee Osteoarthritis (KOA), have a …
especially adults. Among these, bone diseases, including Knee Osteoarthritis (KOA), have a …
[HTML][HTML] From compressed-sensing to artificial intelligence-based cardiac MRI reconstruction
Cardiac magnetic resonance (CMR) imaging is an important tool for the non-invasive
assessment of cardiovascular disease. However, CMR suffers from long acquisition times …
assessment of cardiovascular disease. However, CMR suffers from long acquisition times …
Time-dependent deep image prior for dynamic MRI
We propose a novel unsupervised deep-learning-based algorithm for dynamic magnetic
resonance imaging (MRI) reconstruction. Dynamic MRI requires rapid data acquisition for …
resonance imaging (MRI) reconstruction. Dynamic MRI requires rapid data acquisition for …