AIMC Topic: Proton Magnetic Resonance Spectroscopy
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Unsupervised anomaly detection using generative adversarial networks in H-MRS of the brain.
Journal of magnetic resonance (San Diego, Calif. : 1997)
Feb 13, 2021
The applicability of generative adversarial networks (GANs) capable of unsupervised anomaly detection (AnoGAN) was investigated in the management of quality of H-MRS human brain spectra at 3.0 T. The AnoGAN was trained in an unsupervised manner solel...
Broad Learning Enhanced H-MRS for Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus.
Computational and mathematical methods in medicine
Nov 22, 2020
In this paper, we explore the potential of using the multivoxel proton magnetic resonance spectroscopy (H-MRS) to diagnose neuropsychiatric systemic lupus erythematosus (NPSLE) with the assistance of a support vector machine broad learning system (BL...
Deep learning-based target metabolite isolation and big data-driven measurement uncertainty estimation in proton magnetic resonance spectroscopy of the brain.
Magnetic resonance in medicine
Mar 5, 2020
PURPOSE: The aim of this study was to develop a method for metabolite quantification with simultaneous measurement uncertainty estimation in deep learning-based proton magnetic resonance spectroscopy ( H-MRS).
Reconstruction of spectra from truncated free induction decays by deep learning in proton magnetic resonance spectroscopy.
Magnetic resonance in medicine
Jan 8, 2020
PURPOSE: To explore the applicability of convolutional neural networks (CNNs) in the reconstruction of spectra from truncated FIDs (tFIDs) in H-MRS, which can be valuable in situations in which data sampling is highly limited, such as spectroscopic ...
Intact metabolite spectrum mining by deep learning in proton magnetic resonance spectroscopy of the brain.
Magnetic resonance in medicine
Mar 12, 2019
PURPOSE: To develop a robust method for brain metabolite quantification in proton magnetic resonance spectroscopy ( H-MRS) using a convolutional neural network (CNN) that maps in vivo brain spectra that are typically degraded by low SNR, line broaden...
MultiNet PyGRAPPA: Multiple neural networks for reconstructing variable density GRAPPA (a H FID MRSI study).
NeuroImage
Aug 17, 2018
Magnetic resonance spectroscopic imaging (MRSI) is a powerful tool for mapping metabolite levels across the brain, however, it generally suffers from long scan times. This severely hinders its application in clinical settings. Additionally, the prese...
Multi-class parkinsonian disorders classification with quantitative MR markers and graph-based features using support vector machines.
Parkinsonism & related disorders
Nov 28, 2017
BACKGROUND AND PURPOSE: In this study we attempt to automatically classify individual patients with different parkinsonian disorders, making use of pattern recognition techniques to distinguish among several forms of parkinsonisms (multi-class classi...
Accurate classification of brain gliomas by discriminate dictionary learning based on projective dictionary pair learning of proton magnetic resonance spectra.
Magnetic resonance in chemistry : MRC
Oct 11, 2016
Proton magnetic resonance spectroscopy is a powerful noninvasive technique that complements the structural images of cMRI, which aids biomedical and clinical researches, by identifying and visualizing the compositions of various metabolites within th...
Characterization of dietary fucoxanthin from Himanthalia elongata brown seaweed.
Food research international (Ottawa, Ont.)
Sep 22, 2016
This study explored Himanthalia elongata brown seaweed as a potential source of dietary fucoxanthin which is a promising medicinal and nutritional ingredient. The seaweed was extracted with low polarity solvents (n-hexane, diethyl ether, and chlorofo...
Multiclass imbalance learning: Improving classification of pediatric brain tumors from magnetic resonance spectroscopy.
Magnetic resonance in medicine
Jul 12, 2016
PURPOSE: Classification of pediatric brain tumors from H-magnetic resonance spectroscopy (MRS) can aid diagnosis and management of brain tumors. However, varied incidence of the different tumor types leads to imbalanced class sizes and introduces di...
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