• Investigative Magnetic Resonance Imaging
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• v.13 no.2
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• pp.161-170
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• 2009

Purpose : A parallel imaging method provides us to improve temporal resolution to obtain three-dimensional (3D) MR images. The objective of this study was to optimize three 3D MRI techniques by adjusting 2D SESNE factors of the parallel imaging method in phantom and human brain. Materials and Methods : With a 3 Tesla MRI system and an 8-channel phase-array sensitivity-encoding (SENSE) coil, three 3D MRI techniques of 3D T1-weighted imaging (3D T1WI), 3D T2-weighted imaging (3D T2WI) and 3D fluid attenuated inversion recovery (3D FLAIR) imaging were optimized with adjusting SESNE factors in a water phantom and three human brains. The 2D SENSE factor was applied on the phase-encoding and the slice-encoding directions. Signal-to-noise ratio(SNR), percent signal reduction rate(%R), and contrast-to-noise ratio(CNR) were calculated by using signal intensities obtained in specific regions-of-interest (ROI). Results : In the phantom study, SENSE factor = 3 was provided in 0.2% reduction of signals against without using SENSE with imaging within 5 minutes for 3D T1WI. SENSE factor = 2 was provided in 0.98% signal reduction against without using SENSE with imaging within 5 minutes for 3D T2WI. SENSE factor = 4 was provided in 0.2% signal reduction against without using SENSE with imaging around 6 minutes for 3D FLAIR. In the human brain study, SNR and CNR were higher with SENSE factors = 3 than 4 for all three imaging techniques. Conclusion : This study was performed to optimize 2D SENSE factors in the three 3D MRI techniques that can be scanned in clinical time limitations with minimizing SNR reductions. Without compromising SNR and CNR, the optimum 2D SENSE factors were 3 and 4, yielding the scan time of about 5 to 6 minutes. Further studies are necessary to optimize 3D MRI techniques in other areas in human body.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.2
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• pp.1-6
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• 2003

The study is to automatically or semi-automatically detect the accurate contour of tumors or lesions using active contour models (Snakes) in the MRI images of the brain. In the study we have improved the energy-minimization problem of snakes using dynamic programming and have utilized the values of the canny edge detector by the image force to make the snake less sensitive in noises. For the extracted boundary, the inside area, the perimeter and its center coordinates could be calculated. In addition, the multiple 2D slices with the contour of the lesion wore combined to visualized the shape of the lesion in 3D. We expect that the proposed method in this paper will be useful to make a treatment plan as well as to evaluate the treatments.

• Progress in Medical Physics
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• v.7 no.2
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• pp.67-77
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• 1996

Purpose: To get a 3-D coordinates of intracranial target position was investicated in axial, sagittal and coronal magnetic resonance imaging with a preliminary experimented target localizer. Material and methods : In preliminal experiments, the localizer is made of engineering plastic to avoid the distrubance of magnetic field during the MR image scan. The MR localizer displayed the 9 points in three different axial tomogram. The bright signal of localizer was obtjained from 0.1～0.3％ of paramagnetic gadolinium/DTPA solution in T1WI or T2WI. In this study, the 3-D position of virtual targets were examined from three different axial MR images and the streotactic position was compared to that of BRW stereotactic system in CT scan with same targets. Results: This study provided the actual target position could be obtained from single scan with MRI localizer which has inverse N-typed 9 bars. This experiment was accomplished with shimming test for detection of image distortion in MR image. However we have not found the image distortion in axial scan. The maximum error of target positions showed 1.0 mm in axial, 1.3 mm for sagittal and 1.7 mm for coronal image, respectivelly. The target localization in MR localizer was investicated with spherical virtual target in skull cadaver. Furthermore, the target position was confirmed with CRW stereotactic system showed a 1.3 mm in discrepancy. Summary : The intracranial target position was determined within 1.7 mm of discrepancy with designed MR localizer. We found the target position from axial image has more small discrepancy than that of sagittal and coronal image.

• Progress in Medical Physics
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• v.23 no.2
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• pp.71-80
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• 2012

In order to verify exact dose distributions in the state-of-the-art radiation techniques, a newly designed three-dimensional dosimeter and technique has been took strongly into consideration. The main purpose of our study is to verify the optimized parameters of polymer gel as a real volumetric dosimeter in terms of the various study of MRI. We prepared a gel dosimeter by combing 8% of gelatin, 8% of MAA, and 10 mM of THPC. We used a Co-60 gamma-ray teletherapy unit and delivered doses of 0, 2, 4, 6, 8, 10, 12, and 14 Gy to each polymer gel with a solid phantom. We used a fast spin-echo pulse to acquire the characterized T2 time of MRI. The signal noise ratio (SNR) of the head & neck coil was a relatively lower sensitivity than the body coil; therefore the dose uncertainty of head & neck coil would be lower than body coil's. But the dose uncertainty and resolution of the head & neck coil were superior to the body coil in this study. The TR time between 1,500 ms and 2,000 ms showed no significant difference in the dose resolution, but TR of 1,500 ms showed less dose uncertainty. For the slice thickness of 2.5 mm, less dose uncertainty of TE times was at 4 Gy, as well, it was the lowest result over 4 Gy at TE of 12 ms. The dose uncertainty was not critical up to 6 Gy, but the best dose resolution was obtained at 20 ms up to 8 Gy. The dose resolution shows the lowest value was over 20 ms and was an excellent result in the number of excitation (NEX) of three. The NEX of two was the highest dose resolution. We concluded that the better result of slice thickness versus NEX was related to the NEX increment and thin slice thickness.

• Smart Media Journal
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• v.13 no.4
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• pp.86-93
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• 2024

The development of functional magnetic resonance imaging (fMRI) has significantly contributed to mapping brain functions and understanding brain networks during rest. This paper proposes a CNN-LSTM-based classification model to classify the progression stages of Alzheimer's disease. Firstly, four preprocessing steps are performed to remove noise from the fMRI data before feature extraction. Secondly, the U-Net architecture is utilized to extract spatial features once preprocessing is completed. Thirdly, the extracted spatial features undergo LSTM processing to extract temporal features, ultimately leading to classification. Experiments were conducted by adjusting the temporal dimension of the data. Using 5-fold cross-validation, an average accuracy of 96.4% was achieved, indicating that the proposed method has high potential for identifying the progression of Alzheimer's disease by analyzing fMRI data.

• Proceedings of the Korea Contents Association Conference
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• 2017.05a
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• pp.107-108
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• 2017

3차원 위상대조도 기법의 단점인 긴 검사시간으로 인해 임상적 유용성이 떨어진다. 본 논문은 시간매개변수인 병렬영상기법(Grappa) 변경에 따른 혈류정보의 정량적 평가를 통해 차이점을 알아보고 임상적 활용정도를 평가하였다. 자체 제작한 혈류팬텀을 통해 실험하였으며, Grappa을 5번 변경하여 실험하였다. 연구결과, Grappa를 적용하지 않았을 경우 혈류속도는 평균 9.42로 총 4단계를 적용한 혈류속도 차이율은 각각(1.4, 1.5, 0.4, 1.5%)이었으며 flow와 WSS도 각각(1.4, 1.6, 0.8, 25%), (2.1, 1.4, 1.1, 0.8%)이었다. 통계적으로도 유의하지 않아 Grappa를 적용하지 않은 검사법과 혈류정보가 동일하였다.(P>0.05) 긴 검사 시간으로 인해 임상적 활용이 떨어지는 짧은 검사시간을 요하는 소아환자나 중등도 환자 또는 폐쇄공포증 환자에게 시간을 단축한 3차원 위상대조도 기법을 사용하여 단점을 보완한다면 임상적 활용가치가 높아질 것이라 사료된다.

• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.339-346
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• 2000

Medical image is analyzed to get an anatomical information for diagnostics. Segmentation must be preceded to recognize and determine the lesion more accurately. In this paper, we propose automatic segmentation algorithm for MR brain images using T1-weighted, T2-weighted and PD images complementarily. The proposed segmentation algorithm is first, extracts cerebrum images from 3 input images using cerebrum mask which is made from PD image. And next, find 3D clusters corresponded to cerebrum tissues using scale filtering and 3D clustering in 3D space which is consisted of T1, T2, and PD axis. Cerebrum images are segmented using FCM algorithm with its initial centroid as the 3D cluster's centroid. The proposed algorithm improved segmentation results using accurate cluster centroid as initial value of FCM algorithm and also can get better segmentation results using multi spectral analysis than single spectral analysis.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.267-273
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• 2011

In this paper, we proposed the method to detect brain tumor region in MR images. Our method is composed of 3 parts, detection of tumor slice, detection of tumor region and tumor boundary detection. In the tumor slice detection step, a slice which contains tumor regions is distinguished using symmetric analysis in 3D brain volume. The tumor region detection step is the process to segment the tumor region in the slice distinguished as a tumor slice. And tumor region is finally detected, using spatial feature and symmetric analysis based on the cluster information. The process for detecting tumor slice and tumor region have advantages which are robust for noise and requires less computational time, using the knowledge of the brain tumor and cluster-based on symmetric analysis. And we use the level set method with fast marching algorithm to detect the tumor boundary. It is performed to find the tumor boundary for all other slices using the initial seeds derived from the previous or later slice until the tumor region is vanished. It requires less computational time because every procedure is not performed for all slices.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.1105-1110
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• 2009

To assess the clinical value of time resolved imaging of contrast kinetics(TRICKS) MRA by comparison with conventional time of flight(TOF) MR angiography. Both TOF-MRA and TRICKS-MRA were performed in 17 patients with cerebrovascular disease and in 6 patients with brain tumor. Among 17 cerebraovascular patients, digital subtraction angiography(DSA) data were also obtained in 11 patients. TOF-MRA showed good spatial resolution but short in temporal resolution. Although TRICKS-MRA showed somewhat low spatial resolution, it showed superior temporal resolution by distinguishing vessel and tumor in all patients. Also, from the analysis of vessel-tumor relationship, TRICKS-MRA showed better performance than TOF-MRA. TRICKS-MRA makes it possible to image arterial, capillary and venous phase sequentially with very speedy manner and therefore, the clinical use of this method is highly suggestive for future use.

• Journal of Biomedical Engineering Research
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• v.21 no.4
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• pp.333-338
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• 2000

In this paper, an automated segmentation algorithm is proposed for MR brain images using T1-weighted, T2-weighted, and PD images complementarily. The proposed segmentation algorithm is composed of 3 step. In the first step, cerebrum images are extracted by putting a cerebrum mask upon the three input images. In the second step, outstanding clusters that represent inner tissues of the cerebrum are chosen among 3-dimensional(3D) clusters. 3D clusters are determined by intersecting densely distributed parts of 2D histogram in the 3D space formed with three optimal scale images. Optimal scale image is made up of applying scale space filtering to each 2D histogram and searching graph structure. Optimal scale image best describes the shape of densely distributed parts of pixels in 2D histogram and searching graph structure. Optimal scale image best describes the shape of densely distributed parts of pixels in 2D histogram. In the final step, cerebrum images are segmented using FCM algorithm with its initial centroid value as the outstanding clusters centroid value. The proposed cluster's centroid accurately. And also can get better segmentation results from the proposed segmentation algorithm with multi spectral analysis than the method of single spectral analysis.