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Magnetic Resonance Spectroscopy

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A magnetic resonance conditional robot for lumbar spinal injection: Development and preliminary validation.

The international journal of medical robotics + computer assisted surgery : MRCAS
PURPOSE: This work presents the design and preliminary validation of a Magnetic Resonance (MR) conditional robot for lumbar injection for the treatment of lower back pain.

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

Magma (New York, N.Y.)
PURPOSE: Use a conference challenge format to compare machine learning-based gamma-aminobutyric acid (GABA)-edited magnetic resonance spectroscopy (MRS) reconstruction models using one-quarter of the transients typically acquired during a complete sc...

Frequency and phase correction of GABA-edited magnetic resonance spectroscopy using complex-valued convolutional neural networks.

Magnetic resonance imaging
PURPOSE: To determine the significance of complex-valued inputs and complex-valued convolutions compared to real-valued inputs and real-valued convolutions in convolutional neural networks (CNNs) for frequency and phase correction (FPC) of GABA-edite...

An Update on MR Spectroscopy in Cancer Management: Advances in Instrumentation, Acquisition, and Analysis.

Radiology. Imaging cancer
MR spectroscopy (MRS) is a noninvasive imaging method enabling chemical and molecular profiling of tissues in a localized, multiplexed, and nonionizing manner. As metabolic reprogramming is a hallmark of cancer, MRS provides valuable metabolic and mo...

Fusing H NMR and Raman experimental data for the improvement of wine recognition models.

Food chemistry
The present study proposes the development of new wine recognition models based on Artificial Intelligence (AI) applied to the mid-level data fusion of H NMR and Raman data. In this regard, a supervised machine learning method, namely Support Vector ...

Self-organizing maps for exploration and classification of nuclear magnetic resonance spectra for untargeted metabolomics of breast cancer.

Journal of pharmaceutical and biomedical analysis
Metabolomics has emerged as a powerful tool for identifying biomarkers of disease, and nuclear magnetic resonance (NMR) spectroscopy allows for the simultaneous detection of a wide range of metabolites. However, due to complex interactions within met...

Resolution Enhancement of Metabolomic J-Res NMR Spectra Using Deep Learning.

Analytical chemistry
J-Resolved (J-Res) nuclear magnetic resonance (NMR) spectroscopy is pivotal in NMR-based metabolomics, but practitioners face a choice between time-consuming high-resolution (HR) experiments or shorter low-resolution (LR) experiments which exhibit si...

Enhancing Chemical Reaction Monitoring with a Deep Learning Model for NMR Spectra Image Matching to Target Compounds.

Journal of chemical information and modeling
In the synthetic laboratory, researchers typically rely on nuclear magnetic resonance (NMR) spectra to elucidate structures of synthesized products and confirm whether they match the desired target compounds. As chemical synthesis technology evolves ...

The combination of HSI and NMR techniques with deep learning for identification of geographical origin and GI markers of Lycium barbarum L.

Food chemistry
Lycium barbarum L. (L. barbarum) is renowned worldwide for its nutritional and medicinal benefits. Rapid and accurate identification of L.barbarum's geographic origin is essential because its nutritional content, medicinal efficacy, and market price ...