Improved halbach magnets by particle swarm optimization for mobile nuclear magnetic resonance systems

2013 ◽  
Author(s):  
Yiyuan Cheng ◽  
Ling Xia ◽  
Wei He ◽  
Minhua Zhu ◽  
Feng Liu
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Particle Swarm Optimization ◽  
Magnetic Resonance ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Nuclear Magnetic

scholarly journals Clinical Analysis of Improved Particle Swarm Algorithm-Based Magnetic Resonance Imaging Diagnosis of Placenta Accreta

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Xiaoyan Ding ◽  
Yingying Cao ◽  
Fengtao Sun ◽  
Airong Ma ◽  
Feiyue Zhang
Keyword(s):  
Magnetic Resonance Imaging ◽  
Particle Swarm Optimization ◽  
Magnetic Resonance ◽  
Placenta Accreta ◽  
Particle Swarm ◽  
Clinical Analysis ◽  
Particle Swarm Algorithm ◽  
Resonance Imaging ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization

The magnetic resonance imaging (MRI) image processing capabilities were investigated based on the improved particle swarm optimization (IPSO) algorithm, and the clinical application analysis of MRI images in the diagnosis of placenta accreta (PA) was evaluated in this study. The MRI uterine images were detected on the basis of IPSO. Besides, the clinical data of 89 patients with PA were selected and collected, who were diagnosed by clinical cesarean section surgery and pathological comprehensive diagnosis in hospital from January 2018 to July 2020. Then, all of them underwent the ultrasound (US) and MRI examinations, and the differences of sensitivity, specificity, and accuracy between MRI and US under IPSO in the diagnosis of PA were compared, as well as the differences in the diagnosis of adhesive, implantable, and penetrated PA. The results showed that the difference in detection between IPSO-based MRI images and US images was not statistically substantial ( p > 0.05 ), but the number of initial detections was higher than the number of US examination. MRI examination had higher sensitivity and specificity in the diagnosis of PA during pregnancy, especially for implantable PA, compared with US examination ( p < 0.05 ). In conclusion, MRI images based on the improved particle swarm optimization algorithm showed a good application effect in the diagnosis of placental implantation diseases, which was worthy of further promotion in clinical practice.

Magnetic resonance brain classification by a novel binary particle swarm optimization with mutation and time-varying acceleration coefficients

2016 ◽  
Vol 61 (4) ◽  
pp. 431-441 ◽  
Author(s):  
Shuihua Wang ◽  
Preetha Phillips ◽  
Jianfei Yang ◽  
Ping Sun ◽  
Yudong Zhang
Keyword(s):  
Particle Swarm Optimization ◽  
Magnetic Resonance ◽  
Probabilistic Neural Network ◽  
Particle Swarm ◽  
Binary Particle Swarm Optimization ◽  
Time Varying ◽  
Swarm Optimization ◽  
Average Accuracy ◽  
Mr Brain ◽  
Better Than

Abstract Aim: To develop an automatic magnetic resonance (MR) brain classification that can assist physicians to make a diagnosis and reduce wrong decisions. Method: This article investigated the binary particle swarm optimization (BPSO) approach and proposed its three new variants: BPSO with mutation and time-varying acceleration coefficients (BPSO-MT), BPSO with mutation (BPSO-M), and BPSO with time-varying acceleration coefficients (BPSO-T). We first extracted wavelet entropy (WE) features from both approximation and detail sub-bands of eight-level decomposition. Afterwards, we used the proposed BPSO-M, BPSO-T, and BPSO-MT to select features. Finally, the selected features were fed into a probabilistic neural network (PNN). Results: The proposed BPSO-MT performed better than BPSO-T and BPSO-M. It finally selected two features of entropies of the following two sub-bands (V1, D1). The proposed system “WE + BPSO-MT + PNN” yielded perfect classification on Data160 and Data66. In addition, it yielded 99.53% average accuracy for the Data255, over 10 repetitions of k-fold stratified cross validation (SCV), higher than state-of-the-art approaches. Conclusions: The proposed method is effective for MR brain classification.

An emerging technology: Nuclear magnetic resonance microscopy

1988 ◽  
Vol 46 ◽  
pp. 1000-1001
Author(s):  
M.J. Hennessy ◽  
E. Kwok
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Relaxation Times ◽  
Basic Research ◽  
Local Environment ◽  
Magnetic Resonance Images ◽  
Nmr Microscopy ◽  
Mri Scans ◽  
Temperature Relaxation ◽  
Nuclear Magnetic

Much progress in nuclear magnetic resonance microscope has been made in the last few years as a result of improved instrumentation and techniques being made available through basic research in magnetic resonance imaging (MRI) technologies for medicine. Nuclear magnetic resonance (NMR) was first observed in the hydrogen nucleus in water by Bloch, Purcell and Pound over 40 years ago. Today, in medicine, virtually all commercial MRI scans are made of water bound in tissue. This is also true for NMR microscopy, which has focussed mainly on biological applications. The reason water is the favored molecule for NMR is because water is,the most abundant molecule in biology. It is also the most NMR sensitive having the largest nuclear magnetic moment and having reasonable room temperature relaxation times (from 10 ms to 3 sec). The contrast seen in magnetic resonance images is due mostly to distribution of water relaxation times in sample which are extremely sensitive to the local environment.

Nuclear magnetic resonance microscopy

1989 ◽  
Vol 47 ◽  
pp. 828-829
Author(s):  
Paul C. Lauterbur
Keyword(s):  
Magnetic Field ◽  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Magnetic Fields ◽  
Signal To Noise ◽  
Field Gradients ◽  
Useful Signal ◽  
Magnetic Field Gradients ◽  
Observation Times ◽  
Nuclear Magnetic

Nuclear magnetic resonance imaging can reach microscopic resolution, as was noted many years ago, but the first serious attempt to explore the limits of the possibilities was made by Hedges. Resolution is ultimately limited under most circumstances by the signal-to-noise ratio, which is greater for small radio receiver coils, high magnetic fields and long observation times. The strongest signals in biological applications are obtained from water protons; for the usual magnetic fields used in NMR experiments (2-14 tesla), receiver coils of one to several millimeters in diameter, and observation times of a number of minutes, the volume resolution will be limited to a few hundred or thousand cubic micrometers. The proportions of voxels may be freely chosen within wide limits by varying the details of the imaging procedure. For isotropic resolution, therefore, objects of the order of (10μm) may be distinguished.Because the spatial coordinates are encoded by magnetic field gradients, the NMR resonance frequency differences, which determine the potential spatial resolution, may be made very large. As noted above, however, the corresponding volumes may become too small to give useful signal-to-noise ratios. In the presence of magnetic field gradients there will also be a loss of signal strength and resolution because molecular diffusion causes the coherence of the NMR signal to decay more rapidly than it otherwise would. This phenomenon is especially important in microscopic imaging.

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