• Title/Summary/Keyword: error of magnetic field mapping

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Effect of sensor positioning error on the accuracy of magnetic field mapping result for NMR/MRI

  • Huang, Li;Lee, Sangjin
    • Progress in Superconductivity and Cryogenics
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    • v.17 no.3
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    • pp.28-32
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    • 2015
  • Nowadays the magnetic field mapping is widely used in the design and analysis of the NMR/MRI magnet system, and the accuracy of mapping result has become more and more important. There are several factors affecting the accuracy of the mapping such as the mapping method, the precision of the sensor, the position of the measurement points, the calculation accuracy, and so on. In this paper the error due to the misalignment of the measurement points was discussed. The magnetic field in the central volume was mapped using an indirect method in an MRI magnet system and the magnetic field was fitted to a polynomial. Considering the misalignment between the original measurement points and the practical measurement points, there must be some errors in the mapping calculation and we called it positioning error. Several comparisons of the positioning error have been presented through the theoretical estimates and the exact magnetic field values. Finally, the allowable positioning errors were suggested to guarantee the accuracy of the magnetic field mapping within a certain degree for an example case.

A study on the effect of the condition number in the magnetic field mapping of the Air-Core solenoid

  • Huang, Li;Lee, Sangjin
    • Progress in Superconductivity and Cryogenics
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    • v.17 no.2
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    • pp.31-35
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    • 2015
  • Mapping is a useful tool in the magnetic field analysis and design. In some specific research area, such as the nuclear magnetic resonance (NMR) or the magnetic resonance imaging (MRI), it is important to map the magnetic field in the interesting space with high accuracy. In this paper, an indirect mapping method in the center volume of an air-core solenoid is presented, based on the solution of the Laplace's equation for the field. Through the mathematical analysis on the mapping calculation, we know that the condition number of the matrix, generated by the measurement points, can greatly affect the error of mapping result. Two different arrangement methods of the measurement points in field mapping are described in this paper: helical cylindrical line (HCL) method and parallel cylindrical line (PCL) method. According to the condition number, the HCL method is recommended to measure the field components using one probe. As a simple example, we mapped the magnetic fields in a MRI main magnet system. Comparing the results in the different methods, it is feasible and convenient to apply the condition number to reduce the error in the field mapping calculation. Finally, some guidelines were presented for the magnetic field mapping in the center volume of the air-core solenoid.

Indoor Position Detection Algorithm Based on Multiple Magnetic Field Map Matching and Importance Weighting Method (다중 자기센서를 이용한 실내 자기 지도 기반 보행자 위치 검출 정확도 향상 알고리즘)

  • Kim, Yong Hun;Kim, Eung Ju;Choi, Min Jun;Song, Jin Woo
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.68 no.3
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    • pp.471-479
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    • 2019
  • This research proposes a indoor magnetic map matching algorithm that improves the position accuracy by employing multiple magnetic sensors and probabilistic candidate weighting function. Since the magnetic field is easily distorted by the surrounding environment, the distorted magnetic field can be used for position mapping, and multiple sensor configuration is useful to improve mapping accuracy. Nevertheless, the position error is likely to increase because the external magnetic disturbances have repeated pattern in indoor environment and several points have similar magnetic field distortion characteristics. Those errors cause large position error, which reduces the accuracy of the position detection. In order to solve this problem, we propose a method to reduce the error using multiple sensors and likelihood boundaries that uses human walking characteristics. Also, to reduce the maximum position error, we propose an algorithm that weights according to their importance. We performed indoor walking tests to evaluate the performance of the algorithm and analyzed the position detection error rate and maximum distance error. From the results we can confirm that the accuracy of position detection is greatly improved.

Simultaneous Unwrapping Phase and Error Recovery from Inhomogeneity (SUPER) for Quantitative Susceptibility Mapping of the Human Brain

  • Yang, Young-Joong;Yoon, Jong-Hyun;Baek, Hyun-Man;Ahn, Chang-Beom
    • Investigative Magnetic Resonance Imaging
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    • v.22 no.1
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    • pp.37-49
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    • 2018
  • Purpose: The effect of global inhomogeneity on quantitative susceptibility mapping (QSM) was investigated. A technique referred to as Simultaneous Unwrapping Phase with Error Recovery from inhomogeneity (SUPER) is suggested as a preprocessing to QSM to remove global field inhomogeneity-induced phase by polynomial fitting. Materials and Methods: The effect of global inhomogeneity on QSM was investigated by numerical simulations. Three types of global inhomogeneity were added to the tissue susceptibility phase, and the root mean square error (RMSE) in the susceptibility map was evaluated. In-vivo QSM imaging with volunteers was carried out for 3.0T and 7.0T MRI systems to demonstrate the efficacy of the proposed method. Results: The SUPER technique removed harmonic and non-harmonic global phases. Previously only the harmonic phase was removed by the background phase removal method. The global phase contained a non-harmonic phase due to various experimental and physiological causes, which degraded a susceptibility map. The RMSE in the susceptibility map increased under the influence of global inhomogeneity; while the error was consistent, irrespective of the global inhomogeneity, if the inhomogeneity was corrected by the SUPER technique. In-vivo QSM imaging with volunteers at 3.0T and 7.0T MRI systems showed better definition in small vascular structures and reduced fluctuation and non-uniformity in the frontal lobes, where field inhomogeneity was more severe. Conclusion: Correcting global inhomogeneity using the SUPER technique is an effective way to obtain an accurate susceptibility map on QSM method. Since the susceptibility variations are small quantities in the brain tissue, correction of the inhomogeneity is an essential element for obtaining an accurate QSM.

Magnetic Measurement of PLS Storage Ring Prototype Dipole Magnet (방사광 가속기용 2극 전자석 특성측정 및 보정)

  • 강봉구;박기현;윤종렬;구양모
    • Journal of the Korean Magnetics Society
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    • v.2 no.2
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    • pp.163-168
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    • 1992
  • Results of magnetic measurement of a prototype Storage Ring dipole magnet for the Pohang Light Source (PLS) are summarized. Hall probe mapping and rotating coil methods are used to measure field profiles and integrated field properties. End chamfering experiments are performed on the as-built magnet, which has four removable pole-end pieces, to meet the specifications set from beam dy-namics requirement. The corrected magnet has efficiency of 99.7% at 2.0 GeV excitation ad higher order multipole error levels less than the specifications for all excitations, showing that the magnet has appropriate properties for the PLS Storage Ring.

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GPS/INS Integration and Preliminary Test of GPS/MEMS IMU for Real-time Aerial Monitoring System (실시간 공중 자료획득 시스템을 위한 GPS/MEMS IMU 센서 검증 및 GPS/INS 통합 알고리즘)

  • Lee, Won-Jin;Kwon, Jay-Hyoun;Lee, Jong-Ki;Han, Joong-Hee
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.27 no.2
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    • pp.225-234
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    • 2009
  • Real-time Aerial Monitoring System (RAMS) is to perform the rapid mapping in an emergency situation so that the geoinformation such as orthophoto and/or Digital Elevation Model is constructed in near real time. In this system, the GPS/INS plays an very important role in providing the position as well as the attitude information. Therefore, in this study, the performance of an IMU sensor which is supposed to be installed on board the RAMS is evaluated. And the integration algorithm of GPS/INS are tested with simulated dataset to find out which is more appropriate in real time mapping. According to the static and kinematic results, the sensor shows the position error of 3$\sim$4m and 2$\sim$3m, respectively. Also, it was verified that the sensor performs better on the attitude when the magnetic field sensor are used in the Aerospace mode. In the comparison of EKF and UKF, the overall performances shows not much differences in straight as well as in curved trajectory. However, the calculation time in EKF was appeared about 25 times faster than that of UKF, thus EKF seems to be the better selection in RAMS.

Quantitative Conductivity Estimation Error due to Statistical Noise in Complex $B_1{^+}$ Map (정량적 도전율측정의 오차와 $B_1{^+}$ map의 노이즈에 관한 분석)

  • Shin, Jaewook;Lee, Joonsung;Kim, Min-Oh;Choi, Narae;Seo, Jin Keun;Kim, Dong-Hyun
    • Investigative Magnetic Resonance Imaging
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    • v.18 no.4
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    • pp.303-313
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    • 2014
  • Purpose : In-vivo conductivity reconstruction using transmit field ($B_1{^+}$) information of MRI was proposed. We assessed the accuracy of conductivity reconstruction in the presence of statistical noise in complex $B_1{^+}$ map and provided a parametric model of the conductivity-to-noise ratio value. Materials and Methods: The $B_1{^+}$ distribution was simulated for a cylindrical phantom model. By adding complex Gaussian noise to the simulated $B_1{^+}$ map, quantitative conductivity estimation error was evaluated. The quantitative evaluation process was repeated over several different parameters such as Larmor frequency, object radius and SNR of $B_1{^+}$ map. A parametric model for the conductivity-to-noise ratio was developed according to these various parameters. Results: According to the simulation results, conductivity estimation is more sensitive to statistical noise in $B_1{^+}$ phase than to noise in $B_1{^+}$ magnitude. The conductivity estimate of the object of interest does not depend on the external object surrounding it. The conductivity-to-noise ratio is proportional to the signal-to-noise ratio of the $B_1{^+}$ map, Larmor frequency, the conductivity value itself and the number of averaged pixels. To estimate accurate conductivity value of the targeted tissue, SNR of $B_1{^+}$ map and adequate filtering size have to be taken into account for conductivity reconstruction process. In addition, the simulation result was verified at 3T conventional MRI scanner. Conclusion: Through all these relationships, quantitative conductivity estimation error due to statistical noise in $B_1{^+}$ map is modeled. By using this model, further issues regarding filtering and reconstruction algorithms can be investigated for MREPT.