• Investigative Magnetic Resonance Imaging
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• v.1 no.1
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• pp.51-57
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• 1997

MRI의 artifact는 대부분 신호의 부호화 방향에 따라서 방향성을 가지는데, 이를 요약해보면, 위상부호화 방향의 artifact에는 motion artifact, flow artifact, RF noise등이 있고, 주파수 부호화 방향의 artfact는 susceptibility artfact, chemical shift artifact, central line artifact등이 있으며, 양방향 모두 생길수 있는 것은 Aliasing artifact와 Gibb's phenomenon이고, 전체적으로 영샹의 질을 떨어뜨리는 것은 susceptibility artifact, Eddy current, cross talk등이 있다. 이런 artifact는 대부분은 MRI 자체의 물리적 특성에 다소간 기인하므로, artifact가 없는 양호한 영상을 얻기 위해서는 MRI의 설치 단계부터 관심이 필요하고, MRI의 기본원리와 다양한 artifact에 대해 이해함으로써, 제거 가능한 artifact는 제거하여 양질의 영상을 만들고 판독시의 오류를 피할 수 있도록 해야할 것이다.

• Journal of Biomedical Engineering Research
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• v.41 no.1
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• pp.28-34
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• 2020

In this paper, we introduce motion artifact reduction algorithm for interleaved MRI using an advanced 3D approximation algorithm. The motion artifact framework of this paper is data corrected by post-processing with a new 3-D approximation algorithm which uses data structure for each voxel. In this study, we simulate and evaluate our algorithm using Shepp-Logan phantom and T1-MRI template for both scattered dataset and uniform dataset. We generated motion artifact using random generated motion parameters for the interleaved MRI. In simulation, we use image coregistration by SPM12 (https://www.fil.ion.ucl.ac.uk/spm/) to estimate the motion parameters. The motion artifact correction is done with using full dataset with estimated motion parameters, as well as use only one half of the full data which is the case when the half volume is corrupted by severe movement. We evaluate using numerical metrics and visualize error images.

• Proceedings of the KSMRM Conference
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• 2002.11a
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• pp.97-97
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• 2002

목적： MRI system에서 얻어지는 기초 data는 k-space 즉, 촬영대상의 Fourier Transform된 data이다. MRI를 이용한 단층 영상 촬영에서 촬영도중 촬영대상이 움직일 경우 움직임으로 인해 artifact가 발생하게 된다. 이것은 영상의 질을 떨어뜨림은 물론, 심한 경우에는 영상을 판독하지 못할 정도로 영상의 질에 영향을 미치게 된다. 이 연구에서는 촬영대상의 움직임이 방향성이 한 방향일 경우 그 움직이는 양을 검출하고, 그 결과를 이용하여 움직임으로 인해 생기는 artifact를 보정하는 방법을 제시하고자 한다.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.411-419
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• 2004

When the imaging object rotates in image plane during MRI scan, its rotation causes phase error and non-uniform sampling to MRI signal. The model of the problem including phase error non-uniform sampling of MRI signal showed that the MRI signals corrupted by rotations about an arbitrary center and the origin in image plane are different in their phases. Therefore the following methods are presented to improve the quality of the MR image which includes the artifact. The first, assuming that the angle of 2-D rotational motion is already known and the position of 2-D rotational center is unknown, an algorithm to correct the artifact which is based on the phase correction is presented. The second, in case of 2-D rotational motion with unknown rotational center and unknown rotational angle, an algorithm is presented to correct the MRI artifact. At this case, the energy of an ideal MR image is minimum outside the boundary of the imaging object to estimate unknown motion parameters and the measured energy increases when the imaging object has an rotation. By using this property, an evaluation function is defined to estimate unknown values of rotational angle at each phase encoding step. Finally, the effectiveness of this presented techniques is shown by using a phantom image with simulated motion and a real image with 2-D translational shift and rotation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.53-62
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• 2004

In this study, an improved post-processing technique for correcting MRI artifact due to the unknown respiratory motion in the imaging plane is presented. Respiratory motion is modeled by a two-Dimensional linear expending-shrinking movement. Assuming that the body tissues are incompressible fluid like materials, the proton density per unit volume of the imaging object is kept constant. According to the introduced model, respiratory motion imposes phase error, non-uniform sampling and amplitude modulation distortions on the acquired MRI data. When the motion parameters are known or can be estimatead a reconstruction algorithm based on biliner superposition method was used to correct the MRI artifact. In the case of motion parameters are unknown, first, the spectrum shift method is applied to find the respiratory fluctuation function, x directional expansion coefficient and x directional expansion center. Next, y directional expansion coefficient and y directional expansion center are estimated by using the minimum energy method. Finally, the validity of this proposed method is shown to be effective by using the simulated motion images.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.377-382
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• 1994

In the conventional Fourier imaging method in MRI (Magnetic Resonance Imaging), intramotion such as pulsatile flow makes zipper-like artifact along the phase encoding direction. On the other hand, line-integral projection reconstruction (LPR) method has advantages such as imaging of short T2, object and reduction of the flow artifact by elimination of the flow-induced phase fluctuation. The LPR, however, necessarily requires time consuming filtering and back-projection processes, so that the reconstruction takes long time. To overcome the long reconstruction time of the LPR and to obtain the flow artifact reduction effect, we adopted phase corrected concentric square raster sampling (CSRS) method and improved its imaging performance. The CSRS is a fast reconstruction method which has the same properties with the LPR. In this paper, we proposed a new method of flow artifact reduction using the CSRS method. Through computer simulations and experiments, we verified that the proposed method can eliminate phase fluctuations, thereby reducing the flow artifact and re- markably shorten the reconstruction time which required long time in the LPR.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.227-232
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• 2019

MRI examination for patients with metal objects has in poor image quality. Metallic implants can result in poor image because magnetic susceptibility causes signal loss and distortion and makes poor imaging, which is called magnetic susceptibility artifact or metal artifact. There are several approaches to reduce metal artifacts. In this study, we study the reduction of metal artifact by VAT and SEMAC techniques. A metal implant used for orthopedic surgery was attached to the phatom and the distortion caused by the artifact was measured under T1WI and T2WI protocols. Several techniques of VAT only and VAT and SEMAC for the reduction of metal artifact were compared. The metal artifact showed a reduction of at least 8% to a maximum of 26% in the VAT-SEMAC. The VAT-SEMAC technique can be applied to patients with orthopedic implants to improve image quality. If scan time and image quality are simultaneously considered in VAT-SEMAC technique, metal artifact will be reduced in clinical practice.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.375-385
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• 2016

Recently, several implantable hearing aids such as cochlear implant, middle ear implant, etc., which have a module receiving power and signal from outside the body, are frequently used to treat the hearing impaired patients. Most of implantable hearing aids are adopted permanent magnet pairs to couple between internal and external devices for the enhancement of power transmission. Generally, the internal device which containing the magnet in the center of receiving coil is implanted under the skin of human temporal bone. In case of MRI scanning of a patient with the implantable hearing aid, however, homogeneous magnetic fields of the MRI might be interfered by the implanted magnet. For the above reasons, the MR image is degraded by large area of artifact, so that diagnostics are almost impossible in deteriorated region. In this paper, we proposed an external coil system that can reduce the artifact of MR image due to the internal coupling magnet. By finite element analysis estimating area of MR artifact according to varying current and shape of the external coil, optimal coil parameters were extracted. Finally, the effectiveness of the proposed external coil system was verified by confirming the artifact at real MRI scan.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.49-57
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• 2000

In this study, a new algorithm for canceling a MRI artifact due to the translational motion In the image plane is described. Unlike the conventional iterative phase retrieval algorithm, in which there is no guarantee for the convergence, a direct method for estimating the motion is presented. In previous approaches, the motions in the x(read out) direction and the y(phase encoding) direction were estimated simultaneously. However, the feature of x and y directional motions are different from each other. By analyzing their features, each x and y directional motion is canceled by the different algorithms in two steps. First, it is noticed that the x directional motion corresponds to a shift of the x directional spectrum of the MRI signal, and the non-zero area of the spectrum just corresponds to the projected area of the density function on the x axis. So the motion is estimated by tracing the edges between non-zero area and zero area of the spectrum, and the x directional motion is canceled by shifting the spectrum in an reverse direction. Next, the y directional motion is canceled by using a new constraint condition, with which the motion component and the true image component can be separated. This algorithm is shown to be effective by using a phantom image with simulated motion.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.631-634
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• 1999

In this work, a new algorithm for canceling MRI artifact in the image plane is presented. In the conventional approach, the motions in the X(readout) direction and Y(the phase encoding) direction are estimated simultaneously. However, the feature of each X and Y directional motion is different. First, we notice that the X directional motion corresponds to a shift of the X directional spectrum of the MRI signal, and the non zero area of the spectrum just corresponds to X axis projected area of the density function. So the motion is estimated by tracing the edges of the spectrum, and the X directional motion is canceled by shifting the spectrum in inverse direction. Next, the Y directional motion is canceled using a new constraint, with which the motion component and the true image component can be separated. This algorithm is shown to be effective by simulations.