Magnetic induction method aims at the noninvasive detection of liver iron overload by measuring the hepatic magnetic susceptibility. To solve the difficulty that eddy current effects interfere with the measurement of magnetic susceptibility, we proposed an improved coil system based on the static field magnetization principle in this study. We used a direct current excitation to eliminate the eddy current effect, and a rotary receiver coil to get the induced voltage. The magnetic field for a cylindrical object due to the magnetization effect was calculated and the relative change of maximum induced voltage was derived. The correlation between magnetic susceptibility of object and maximum magnetic flux, maximum induced voltage and relative change of maximum induced voltage of the receiver coil were obtained by simulation experiments, and the results were compared with those of the theory calculation. The contrast shows that the simulation results fit the theory results well, which proves our method can eliminate the eddy current effect effectively.
Quantitative magnetic susceptibility imaging (QSM) is an imaging method based on magnetic resonance imaging (MRI) phase signal processing and inversion to obtain tissue magnetic susceptibility distribution, which can generate images reflecting the magnetic characteristics of tissues. QSM reconstruction process is complex, in which dipole inversion stage is the most challenging and decisive link, and traditional methods are easily affected by pathological conditions at this stage, resulting in artifacts and deviations. With the development of deep learning and machine vision technology, using U-network (U-Net) model to improve dipole inversion process can effectively avoid the shortcomings of traditional algorithms. In this paper, the application of the improved model based on U-Net architecture in dipole inversion from 2020 to now is summarized. Firstly, the theoretical concept of QSM is introduced. Secondly, the existing improved models based on U-Net architecture are divided into three categories: improved U-Net based on structural optimization, improved U-Net based on physical constraints and improved U-Net based on improving generalization ability, and their main characteristics and design starting points are sorted out. Finally, the development trend of the future model is prospected and summarized. To sum up, it is expected that the difficulties and challenges of dipole inversion will be solved, the accuracy of QSM images will be improved, and support for disease-aided diagnosis will be provided by summarizing and comparing different improved U-Net models in this paper.
Magnetic susceptibility is an intrinsic physical quantity which describes the relationship between material magnetization and applied external magnetic field. Quantitative susceptibility mapping (QSM) is an MRI technology which can quantify the buck magnetic susceptibility of tissue in vivo. It is particularly effective at elucidating anatomy with paramagnetic or diamagnetic components. QSM technology is a method for solving the ill-pose problem of un-conventional de-convolution of the measured tissue magnetic field with the unit magnetic dipole field to obtain the susceptibility source map. Many multi orientation scan based QSM and clinically acceptable single orientation QSM methods have been proposed to solve this ill-posed problem. In this paper, the QSM concept is introduced and the various QSM methods are systematically categorized and discussed. The aim of this paper is to summarize the current research progress of QSM, popularize the knowledge of QSM and promote the improvements and the rational application of QSM in clinical field.
