• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.4
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• pp.30-39
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• 2010

Since Diffusion tensor from Diffusion Tensor Magnetic Resonance Imaging(DT-MRI) is so sensitive to noise, the principle eigenvector(PEV) calculated from Diffusion tensor could be erroneous. Tractography obtained from PEV could be deviated from the real fiber tract. Therefore regularization process is needed to eliminate noise. In this paper, to reduce noise in DT-MRI measurements, the Dyadic Sorting(DS) method as regularization of the eigenvalue and the eigenvector is applied in the tractography. To resort the eigenvalues and the eignevectors, the DS method uses the intervoxel overlap function which can measure the overlap between eigenvalue-eigenvector pairs in the $3\times3$ pixel. In this paper, we applied the DS method to the three-dimensional volume. We discuss the error analysis and numerical study to the synthetic and the experimental data. As a result, we have shown that the DS method is more efficient than the median filtering methods as much as 79.97%~83.64%, 85.62%~87.76% in AAE, AFA respectively for the corticospinal tract of the experimental data.

• Journal of Biomedical Engineering Research
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• v.28 no.6
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• pp.817-824
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• 2007

Tractography using Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) is a method to determine the architecture of axonal fibers in the central nervous system by computing the direction of the principal eigenvector in the white matter of the brain. However, the fiber tracking methods suffer from the noise included in the diffusion tensor images that affects the determination of the principal eigenvector. As the fiber tracking progresses, the accumulated error creates a large deviation between the calculated fiber and the real fiber. This problem of the DT-MRI tractography is known mathematically as the ill-posed problem which means that tractography is very sensitive to perturbations by noise. To reduce the noise in DT-MRI measurements, a tensor-valued median filter which is reported to be denoising and structure-preserving in fiber tracking, is applied in the tractography. In this paper, we proposed the modified gradient descent method which converges fast and accurately to the optimal tensor-valued median filter by changing the step size. In addition, the performance of the modified gradient descent method is compared with others. We used the synthetic image which consists of 45 degree principal eigenvectors and the corticospinal tract. For the synthetic image, the proposed method achieved 4.66%, 16.66% and 15.08% less error than the conventional gradient descent method for error measures AE, AAE, AFA respectively. For the corticospinal tract, at iteration number ten the proposed method achieved 3.78%, 25.71 % and 11.54% less error than the conventional gradient descent method for error measures AE, AAE, AFA respectively.

• Journal of the Korean Society of Radiology
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• v.11 no.5
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• pp.343-351
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• 2017

T1, T2 relaxation time and relaxation rates were measured and analyzed according to the change of RF coil channel number of MAGiC sequence. T1, T2, R1 and R2 maps were obtained by using MAGiC sequence with phantom (1.0, 0.6, 0.2, 0 mM) on the RF coil with channel number of 1, 8, 16 and 32 respectively. T1, T2, R1, R2 values and relaxation rates were measured for each channel number and concentration, and Relaxivity was calculated according to each concentration. T1, T2, R1, and R2 values were measured in each coil. There was no significant difference between T1 and R1 values (p> 0.05). However, T2 and R2 values were significantly different (p <0.05). In the post-analysis results, T2 value was significantly different from that measured on 1, 8, 16, and 32 channel coils (p <0.05) and There was no difference between 8, 16, and 32 channel coils (p> 0.05). The R2 value was significantly different from that measured on the 8, 16, and 32 channel coils in the 1 channel coil, and the results on the 8 channel coils and the 16 channel coils showed a significant difference (P <0.05). In conclusion, T1 and R1 values were not significantly different according to the number of channels in the coil, but T2 and R2 values were significantly different. Therefore, when quantitative measurement of T2 and R2 values using the MAGiC sequence, the same number of coils should be used for reproducibility.