| no |
title |
author |
magazine |
year |
volume |
issue |
page(s) |
type |
| 1 |
Artificial intelligence for neuro MRI acquisition: a review
|
Yang, Hongjia
|
|
|
37 |
3 |
p. 383-396
|
article
|
| 2 |
Automated abdominal adipose tissue segmentation and volume quantification on longitudinal MRI using 3D convolutional neural networks with multi-contrast inputs
|
Kafali, Sevgi Gokce
|
|
|
37 |
3 |
p. 491-506
|
article
|
| 3 |
Comparison of convolutional-neural-networks-based method and LCModel on the quantification of in vivo magnetic resonance spectroscopy
|
Huang, Yu-Long
|
|
|
37 |
3 |
p. 477-489
|
article
|
| 4 |
Deep learning-based super-resolution of structural brain MRI at 1.5 T: application to quantitative volume measurement
|
Suwannasak, Atita
|
|
|
37 |
3 |
p. 465-475
|
article
|
| 5 |
Deep learning for accelerated and robust MRI reconstruction
|
Heckel, Reinhard
|
|
|
37 |
3 |
p. 335-368
|
article
|
| 6 |
ESMRMB 2024 focus topic “MR Beyond Structures: The dynamic body at different scales”
|
Pinto, Joana
|
|
|
37 |
3 |
p. 319
|
article
|
| 7 |
ESMRMB 2024 focus topic: MR beyond trends—fact-checking MR
|
Langkammer, Christian
|
|
|
37 |
3 |
p. 321-322
|
article
|
| 8 |
Improvement of image quality in diffusion-weighted imaging with model-based deep learning reconstruction for evaluations of the head and neck
|
Fujima, Noriyuki
|
|
|
37 |
3 |
p. 439-447
|
article
|
| 9 |
Large-scale 3D non-Cartesian coronary MRI reconstruction using distributed memory-efficient physics-guided deep learning with limited training data
|
Zhang, Chi
|
|
|
37 |
3 |
p. 429-438
|
article
|
| 10 |
Learning to deep learning: statistics and a paradigm test in selecting a UNet architecture to enhance MRI
|
Sharma, Rishabh
|
|
|
37 |
3 |
p. 507-528
|
article
|
| 11 |
MR beyond diagnostics at the ESMRMB annual meeting: MR theranostics and intervention
|
Hájek, Milan
|
|
|
37 |
3 |
p. 323-328
|
article
|
| 12 |
Results of the 2023 ISBI challenge to reduce GABA-edited MRS acquisition time
|
Berto, Rodrigo Pommot
|
|
|
37 |
3 |
p. 449-463
|
article
|
| 13 |
Spinet-QSM: model-based deep learning with schatten p-norm regularization for improved quantitative susceptibility mapping
|
Venkatesh, Vaddadi
|
|
|
37 |
3 |
p. 411-427
|
article
|
| 14 |
Stop moving: MR motion correction as an opportunity for artificial intelligence
|
Zhou, Zijian
|
|
|
37 |
3 |
p. 397-409
|
article
|
| 15 |
The beating heart: artificial intelligence for cardiovascular application in the clinic
|
Villegas-Martinez, Manuel
|
|
|
37 |
3 |
p. 369-382
|
article
|
| 16 |
The intelligent imaging revolution: artificial intelligence in MRI and MRS acquisition and reconstruction
|
Küstner, Thomas
|
|
|
37 |
3 |
p. 329-333
|
article
|
Journal description