Detalhe da pesquisa
1.
A generic deep learning model for reduced gadolinium dose in contrast-enhanced brain MRI.
Magn Reson Med
; 86(3): 1687-1700, 2021 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-33914965
2.
Joint multi-contrast variational network reconstruction (jVN) with application to rapid 2D and 3D imaging.
Magn Reson Med
; 84(3): 1456-1469, 2020 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-32129529
3.
Ultra-Low-Dose 18F-Florbetaben Amyloid PET Imaging Using Deep Learning with Multi-Contrast MRI Inputs.
Radiology
; 290(3): 649-656, 2019 03.
Artigo
em Inglês
| MEDLINE | ID: mdl-30526350
4.
JOURNAL CLUB: Use of Gradient Boosting Machine Learning to Predict Patient Outcome in Acute Ischemic Stroke on the Basis of Imaging, Demographic, and Clinical Information.
AJR Am J Roentgenol
; 212(1): 44-51, 2019 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-30354266
5.
Quantitative susceptibility mapping using deep neural network: QSMnet.
Neuroimage
; 179: 199-206, 2018 10 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-29894829
6.
Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI.
J Magn Reson Imaging
; 48(2): 330-340, 2018 08.
Artigo
em Inglês
| MEDLINE | ID: mdl-29437269
7.
A dynamically assembled cell wall synthesis machinery buffers cell growth.
Proc Natl Acad Sci U S A
; 111(12): 4554-9, 2014 Mar 25.
Artigo
em Inglês
| MEDLINE | ID: mdl-24550500
8.
Ultra-Low-Dose 18F-Florbetaben Amyloid PET Imaging Using Deep Learning with Multi-Contrast MRI Inputs.
Radiology
; 296(3): E195, 2020 Sep.
Artigo
em Inglês
| MEDLINE | ID: mdl-32804601
9.
PROMISE: parallel-imaging and compressed-sensing reconstruction of multicontrast imaging using SharablE information.
Magn Reson Med
; 73(2): 523-35, 2015 Feb.
Artigo
em Inglês
| MEDLINE | ID: mdl-24604305
10.
One Model to Synthesize Them All: Multi-Contrast Multi-Scale Transformer for Missing Data Imputation.
IEEE Trans Med Imaging
; 42(9): 2577-2591, 2023 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-37030684
11.
Clinical Assessment of Deep Learning-based Super-Resolution for 3D Volumetric Brain MRI.
Radiol Artif Intell
; 4(2): e210059, 2022 Mar.
Artigo
em Inglês
| MEDLINE | ID: mdl-35391765
12.
Low-count whole-body PET with deep learning in a multicenter and externally validated study.
NPJ Digit Med
; 4(1): 127, 2021 Aug 23.
Artigo
em Inglês
| MEDLINE | ID: mdl-34426629
13.
Applying Deep Learning to Accelerated Clinical Brain Magnetic Resonance Imaging for Multiple Sclerosis.
Front Neurol
; 12: 685276, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-34646227
14.
Predicting 15O-Water PET cerebral blood flow maps from multi-contrast MRI using a deep convolutional neural network with evaluation of training cohort bias.
J Cereb Blood Flow Metab
; 40(11): 2240-2253, 2020 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-31722599
15.
Synthesize High-Quality Multi-Contrast Magnetic Resonance Imaging From Multi-Echo Acquisition Using Multi-Task Deep Generative Model.
IEEE Trans Med Imaging
; 39(10): 3089-3099, 2020 10.
Artigo
em Inglês
| MEDLINE | ID: mdl-32286966
16.
Use of Deep Learning to Predict Final Ischemic Stroke Lesions From Initial Magnetic Resonance Imaging.
JAMA Netw Open
; 3(3): e200772, 2020 03 02.
Artigo
em Inglês
| MEDLINE | ID: mdl-32163165
17.
Ultra-low-dose PET reconstruction using generative adversarial network with feature matching and task-specific perceptual loss.
Med Phys
; 46(8): 3555-3564, 2019 Aug.
Artigo
em Inglês
| MEDLINE | ID: mdl-31131901
18.
Deep Generative Adversarial Neural Networks for Compressive Sensing MRI.
IEEE Trans Med Imaging
; 38(1): 167-179, 2019 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-30040634
19.
Erratum: "Ultra-low-dose PET reconstruction using generative adversarial network with feature matching and task-specific perceptual loss".
Med Phys
; 50(9): 5932, 2023 Sep.
Artigo
em Inglês
| MEDLINE | ID: mdl-37689088
20.
ISLES 2016 and 2017-Benchmarking Ischemic Stroke Lesion Outcome Prediction Based on Multispectral MRI.
Front Neurol
; 9: 679, 2018.
Artigo
em Inglês
| MEDLINE | ID: mdl-30271370