Application of Remote Filtering to Magnetic Resonance Sounding Using Multi‐Channel Data Acquisition

2011 ◽  
Author(s):  
Jean‐Francois Girard ◽  
Jean Bernard ◽  
Benoit Texier
Keyword(s):  
Magnetic Resonance ◽  
Data Acquisition ◽  
Magnetic Resonance Sounding

scholarly journals Electromagnetic Noise Suppression of Magnetic Resonance Sounding Combined with Data Acquisition and Multi-Frame Spectral Subtraction in the Frequency Domain

Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1254
Author(s):  
Tingting Lin ◽  
Xiaokang Yao ◽  
Sijia Yu ◽  
Yang Zhang
Keyword(s):  
Magnetic Resonance ◽  
Data Acquisition ◽  
Frequency Domain ◽  
Noise Suppression ◽  
Random Noise ◽  
Spectral Subtraction ◽  
Signal Acquisition ◽  
Noisy Signal ◽  
Electromagnetic Noise ◽  
Magnetic Resonance Sounding

As an advanced groundwater detection method, magnetic resonance sounding (MRS) has received more and more attention. However, the biggest challenge is that MRS measurements always suffer with a bad signal-to-noise ratio (SNR). Aiming at the problem of noise interference in MRS measurement, we propose a novel noise-suppression approach based on the combination of data acquisition and multi-frame spectral subtraction (DA-MFSS). The pure ambient noise from the measurement area is first collected by the receiving coil, and then the noisy MRS signal is recorded following the pulse moments transmitting. The procedure of the pure noise and the noisy MRS signal acquisition will be repeated several times. Then, the pure noise and the noisy signal are averaged to preliminarily suppress the noise. Secondly, the averaged pure noise and the noisy signal are divided into multiple frames. The framed signal is transformed into the frequency domain and the spectral subtraction method is applied to further suppress the electromagnetic noise embedded in the noisy MRS signal. Finally, the de-noised signal is recovered by the overlap-add method and inverse Fourier transformation. The approach was examined by numerical simulation and field measurements. After applying the proposed approach, the SNR of the MRS data was improved by 16.89 dB and both the random noise and the harmonic noise were well suppressed.

scholarly journals Metabolomics in nutrition research–a powerful window into nutritional metabolism

2016 ◽  
Vol 60 (5) ◽  
pp. 451-458 ◽  
Author(s):  
Lorraine Brennan
Keyword(s):  
Mass Spectrometry ◽  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Data Acquisition ◽  
Small Molecules ◽  
Biological Samples ◽  
Metabolic Pathways ◽  
Recent Trend ◽  
Disease States ◽  
Nutrition Research

Metabolomics is the study of small molecules present in biological samples. In recent years it has become evident that such small molecules, called metabolites, play a key role in the development of disease states. Furthermore, metabolomic applications can reveal information about alterations in certain metabolic pathways under different conditions. Data acquisition in metabolomics is usually performed using nuclear magnetic resonance (NMR)-based approaches or mass spectrometry (MS)-based approaches with a more recent trend including the application of multiple platforms in order to maximise the coverage in terms of metabolites measured. The application of metabolomics is rapidly increasing and the present review will highlight applications in nutrition research.

scholarly journals Application of Magnetic Resonance Image Intelligent Data Acquisition in Ovarian Cancer (Preprint)

2020 ◽  
Author(s):  
Tingting Liang ◽  
Yanlei Dong ◽  
Xinrui Zhao ◽  
Lu Wang ◽  
Hui Xu ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Magnetic Resonance ◽  
Epithelial Cells ◽  
Data Acquisition ◽  
Cell Lines ◽  
P53 Protein ◽  
Control Group ◽  
Ovarian Epithelial Cells ◽  
Intelligent Data Acquisition ◽  
Experimental Group

UNSTRUCTURED As a diagnostic method with no radiation, high resolution of soft tissue, and different imaging methods, Magnetic Resonance Imaging (MRI) intelligent data acquisition is more and more widely used in the examination of abdominal, pelvic, and other organ lesions. In order to study the diagnostic effect of multi-mode magnetic resonance intelligent data acquisition on ovarian cancer and the ovarian cancer model modified based on p53-/-+Myc+ASAP1 gene, NSG mice were selected as experimental subjects in this study. 293FT cell lines packaging p53, Myc, and ASAP1(ArfGAP with SH3 domain, Ankyrin repeat and PH domain 1) recombinant lentivirus were inoculated into mouse ovarian epithelial cells to construct mouse ovarian epithelial cell tumor cell lines and their performance was analyzed. According to the different injection cell lines, they were divided into the experimental group and the control group. Tumor samples were collected and the mice were analyzed using immunofluorescence staining and MRI. The results showed that, in the detection of protein expression in genetically modified cell lines, for p53-/-+Myc+ASAP1 fully modified cell lines, the high expression of ASAP1 and Myc functional proteins was detected after the lentivirus containing p53-/-, ASAP1, and Myc were introduced into mouse ovarian epithelial cells, while the expression of p53 protein decreased significantly; after inoculation into mice, it was found that the expression of ASAP1 protein and Myc protein in the experimental group was significantly higher than that in the control group, while the expression of p53 protein in the experimental group was significantly lower than that in the control group, with significant statistical difference; further MRI diagnosis of two groups of mice showed that the ADC (Apparent dispersion coefficient) value of the experimental group was significantly higher than the control group, there were statistically significant differences. Therefore, it was found that p53 gene expression was down-regulated and Myc and ASAPl genes were overexpressed in the tumor tissues and tumor cells formed, and tumor formation differences between the two groups of mice could be obviously found after MRI intelligent data acquisition, which provided experimental basis for early diagnosis of breast cancer in the later clinical stage.

Focused Multi-layer Inversion of Magnetic Resonance Sounding Data

2013 ◽  
Author(s):  
G. Vignoli ◽  
G. Fiandaca ◽  
A.A. Behroozmand ◽  
E. Auken
Keyword(s):  
Magnetic Resonance ◽  
Magnetic Resonance Sounding

scholarly journals Magnetic resonance sounding measurements as posterior information to condition hydrological model parameters: Application to a hard-rock headwater catchment

2020 ◽  
Vol 587 ◽  
pp. 124941 ◽  
Author(s):  
Nolwenn Lesparre ◽  
Jean-François Girard ◽  
Benjamin Jeannot ◽  
Sylvain Weill ◽  
Marc Dumont ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Hydrological Model ◽  
Hard Rock ◽  
Model Parameters ◽  
Magnetic Resonance Sounding ◽  
Headwater Catchment
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