[HTML][HTML] Spectro-vit: A vision transformer model for gaba-edited mega-press reconstruction using spectrograms

G Dias, RP Berto, M Oliveira, L Ueda, S Dertkigil… - Magnetic Resonance …, 2024 - Elsevier
This study investigated the use of a Vision Transformer (ViT) for reconstructing GABA-edited
Magnetic Resonance Spectroscopy (MRS) data from a reduced number of transients …

CloudBrain-MRS: An intelligent cloud computing platform for in vivo magnetic resonance spectroscopy preprocessing, quantification, and analysis

X Chen, J Li, D Chen, Y Zhou, Z Tu, M Lin… - Journal of Magnetic …, 2024 - Elsevier
Magnetic resonance spectroscopy (MRS) is an important clinical imaging method for
diagnosis of diseases. MRS spectrum is used to observe the signal intensity of metabolites …

Magnetic Resonance Spectroscopy Quantification Aided by Deep Estimations of Imperfection Factors and Macromolecular Signal

D Chen, M Lin, H Liu, J Li, Y Zhou… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Objective: Magnetic Resonance Spectroscopy (MRS) is an important technique for
biomedical detection. However, it is challenging to accurately quantify metabolites with …

Beyond traditional magnetic resonance processing with artificial intelligence

A Jahangiri, V Orekhov - Communications Chemistry, 2024 - nature.com
Smart signal processing approaches using Artificial Intelligence are gaining momentum in
NMR applications. In this study, we demonstrate that AI offers new opportunities beyond …

Results of the 2023 ISBI challenge to reduce GABA-edited MRS acquisition time

RP Berto, H Bugler, G Dias, M Oliveira, L Ueda… - … Resonance Materials in …, 2024 - Springer
Purpose Use a conference challenge format to compare machine learning-based gamma-
aminobutyric acid (GABA)-edited magnetic resonance spectroscopy (MRS) reconstruction …

WAND: Wavelet Analysis-based Neural Decomposition of MRS Signals for Artifact Removal

JP Merkofer, DMJ van de Sande, S Amirrajab… - arXiv preprint arXiv …, 2024 - arxiv.org
Accurate quantification of metabolites in magnetic resonance spectroscopy (MRS) is
challenged by low signal-to-noise ratio (SNR), overlapping metabolites, and various …

Application of a 1H brain MRS benchmark dataset to deep learning for out-of-voxel artifacts

AT Gudmundson, CW Davies-Jenkins… - Imaging …, 2023 - direct.mit.edu
Neural networks are potentially valuable for many of the challenges associated with MRS
data. The purpose of this manuscript is to describe the AGNOSTIC dataset, which contains …

[HTML][HTML] Cloud-magnetic resonance imaging system: in the era of 6G and artificial intelligence

Y Zhou, Y Wu, Y Su, J Li, J Cai, Y You, J Zhou… - Magnetic Resonance …, 2024 - Elsevier
Magnetic resonance imaging (MRI) plays an important role in medical diagnosis, generating
petabytes of image data annually in large hospitals. This voluminous data stream requires a …

An Investigation of Different Deep Learning Pipelines for GABA-Edited MRS Reconstruction

R Berto, H Bugler, R Souza, A Harris - International Workshop on Machine …, 2023 - Springer
Edited magnetic resonance spectroscopy (MRS) can provide localized information on
gamma-aminobutyric acid (GABA) concentration in vivo. However, edited-MRS scans are …

Spectro-ViT: A Vision Transformer Model for GABA-edited MRS Reconstruction Using Spectrograms

G Dias, RP Berto, M Oliveira, L Ueda, S Dertkigil… - arXiv preprint arXiv …, 2023 - arxiv.org
Purpose: To investigate the use of a Vision Transformer (ViT) to reconstruct/denoise GABA-
edited magnetic resonance spectroscopy (MRS) from a quarter of the typically acquired …