Learning to deep learning: statistics and a paradigm test in selecting a UNet architecture to enhance MRI
Objective This study aims to assess the statistical significance of training parameters in 240
dense UNets (DUNets) used for enhancing low Signal-to-Noise Ratio (SNR) and …
dense UNets (DUNets) used for enhancing low Signal-to-Noise Ratio (SNR) and …
A deep learning approach to upscaling “low-quality” MR Images: an in silico comparison study based on the UNet framework
MR scans of low-gamma X-nuclei, low-concentration metabolites, or standard imaging at
very low field entail a challenging tradeoff between resolution, signal-to-noise, and …
very low field entail a challenging tradeoff between resolution, signal-to-noise, and …
[HTML][HTML] Beyond Nyquist: A Comparative Analysis of 3D Deep Learning Models Enhancing MRI Resolution
High-spatial resolution MRI produces abundant structural information, enabling highly
accurate clinical diagnosis and image-guided therapeutics. However, the acquisition of high …
accurate clinical diagnosis and image-guided therapeutics. However, the acquisition of high …
Fourier PD and PDUNet: Complex-valued networks to speed-up MR Thermometry during Hypterthermia
Hyperthermia (HT) in combination with radio-and/or chemotherapy has become an accepted
cancer treatment for distinct solid tumour entities. In HT, tumour tissue is exogenously …
cancer treatment for distinct solid tumour entities. In HT, tumour tissue is exogenously …
Let UNet Play an Adversarial Game: Investigating the Effect of Adversarial Training in Enhancing Low-Resolution MRI
Adversarial training has attracted much attention in enhancing the visual realism of images,
but its efficacy in clinical imaging has not yet been explored. This work investigated …
but its efficacy in clinical imaging has not yet been explored. This work investigated …
Dense U-Nets for Enhancement of Undersampled MRI Using Cross-Contrast Feature Transfer
MRI suffers from an inherent trade-off between signal-to-noise ratio, acquisition time, and
spatial resolution [1]–[3]. K-space undersampling allows for a reduction in acquisition time at …
spatial resolution [1]–[3]. K-space undersampling allows for a reduction in acquisition time at …
[PDF][PDF] Tsiam rtzis, P
R Sharma - Webb,. G., Leiss, EL, & Tsekos, NV, 2023 - scholarlypublications …
Objective This study aims to assess the statistical significance of training parameters in 240
dense UNets (DUNets) used for enhancing low Signal-to-Noise Ratio (SNR) and …
dense UNets (DUNets) used for enhancing low Signal-to-Noise Ratio (SNR) and …
MATNet: MRI Super-Resolution with Multiple Attention Mechanisms
L Shen, F Qin, Y Zhang, Q Wang, B Hu… - … Conference on New …, 2023 - ieeexplore.ieee.org
High-resolution magnetic resonance imaging (MRI) provides a clear anatomical structure for
diagnosis, however, its high cost makes it unsuitable in practice. On the contrary, low …
diagnosis, however, its high cost makes it unsuitable in practice. On the contrary, low …
[引用][C] Image Registration of Dynamic MRI for Strain Analysis of Soft Tissue Structures in the Knee Joint using Elastix
AM Arias-Lorzaa, M Leskovara, M Muhammada…