• Proceedings of the KSMRM Conference
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• 2006.11a
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• pp.71-71
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• 2006

• Investigative Magnetic Resonance Imaging
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• v.9 no.1
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• pp.2-8
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• 2005

Purpose : The purpose of this study was to implement a software to visualize tumor and its surrounding fiber tracts simultaneously using diffusion tensor imaging and examine the feasibility of our software for investigating the influence of tumor on its surrounding fiber connectivity. Material and Methods : MR examination including T1-weigted and diffusion tensor images of a patient with brain tumor was performed on a 3.0 T MRI unit. We used the skull-striped brain and segmented tumor images for volume/surface rendering and anatomical information from contrast-enhanced T1-weighted images. Diffusion tensor images for the white matter fiber-tractography were acquired using a SE-EPI with a diffusion scheme of 25 directions. Fiber-tractography was performed using the streamline and tensorline methods. To correct a spatial mismatch between T1-weighted and diffusion tensor images, they were coregistered using a SPM. Our software was implemented under window-based PC system. Results : We successfully implemented the integrated visualization of the fiber tracts with tube-like surfaces, cortical surface and the tumor with volume/surface renderings in a patient with brain tumor. Conclusion : Our result showed the feasibility of the integrated visualization of brain tumor and its surrounding fiber tracts. In addition, our implementation for integrated visualization can be utilized to navigate the brain for the quantitative analysis of fractional anisotropy to assess changes in the white matter tract integrity of edematic and peri-edematic regions in a number of tumor patients.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.439-445
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• 2004

Diffusion tensor image(DTI) exploits the random diffusional motion of water molecules. This method is useful for the characterization of the architecture of tissues. In some tissues, such as muscle or cerebral white matter, cellular arrangement shows a strongly preferred direction of water diffusion, i.e., the diffusion is anisotropic. The degree of anisotropy is often represented using diffusion anisotropy indices (relative anisotropy(RA), fractional anisotropy(FA), volume ratio(VR)). In this study, FA images were obtained using different gradient schemes(N=6, 11, 23, 35. 47). Mean values and the standard deviations of FA were then measured at several anatomic locations for each scheme. The results showed that both mean values and the standard deviations of FA were decreased as the number of gradient directions were increased. Also, the standard error of ADC measurement decreased as the number of diffusion gradient directions increased. In conclusion, different gradient schemes showed a significantly different noise performance and the schem with more gradient directions clearly improved the quality of the FA images. But considering acquisition time of image and standard deviation of FA, 23 gradient directions is clinically optimal.

• Journal of the Korean Society of Radiology
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• v.12 no.1
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• pp.93-100
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• 2018

The fractional anisotropy value of the brain white matter region was analyzed by Tract-Based Spatial Statics(TBSS) method after acquiring the diffusion tensor image to identify the presence or absence of brain white matter damage to smoking in male. As a result, smokers showed lower fractional anisotropy than non-smokers in all areas but fractional anisotropy values were not statistically significant. the fractional anisotropy value, on the other hand, was statistically significant only for the right choroid plexus. In other words smoking, although, does not significantly affect the micro structural changes of brain white matter, it affects the choroid plexus area.

• Proceedings of the KSMRM Conference
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• 2004.09a
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• pp.61-63
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• 2004

• Proceedings of the KSMRM Conference
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• 2008.04a
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• pp.76-81
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• 2008

• Investigative Magnetic Resonance Imaging
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• v.10 no.1
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• pp.1-7
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• 2006

Purpose : Recent development of diffusion tensor imaging enables the evaluation of the microstructural characteristics of the brain white matter. However, optimal imaging parameters for diffusion tensor imaging, particularly concerning the number of diffusion gradient direction, have not been studied thoroughly yet. The purpose of this study was to evaluate the influence of the number of diffusion gradient direction on the fiber tracking of the white matter. Materials and methods : 13 healthy volunteers (ten men and three women, mean age 30 years, age range 23-37 years) were included in this study. Diffusion tensor imaging was performed with different numbers of diffusion gradient direction as 6, 15, and 32, keeping the other imaging parameters constant. The imaging field ranged from 1 cm below the pons to 2-3 cm above the lateral ventricle, parallel to the anterior commissure-posterior commissure line. FA (fractional anisotropy) maps were created via image postprocessing, and then FA and its standard deviation were calculated in the genu and the splenium of the corpus callosum on each of FA maps. Fiber tracking of the corticospinal tract in the brain was performed and the number of the reconstructed fibers of the tract was measured. FA, standard deviation of FA and the number of the reconstructed fibers were compared statistically between the different diffusion gradient directions. Results : FA is not statistically significantly different between the different diffusion gradient directions. By increasing the number of diffusion gradient direction, standard deviation of FA decreased significantly, and the number of the reconstructed fibers increased significantly. Conclusion : The higher number of diffusion gradient direction provided better quality of fiber tracking.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.753-756
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• 2014

파킨슨병은 도파민계 신경이 파괴되는 질병으로 알츠하이머병과 함께 대표적인 퇴행성 뇌 질환으로 병의 진행을 완화시킬 수 있는 치료법이 존재하기 때문에 병의 진단이 굉장히 중요하다. 파킨슨병을 진단하기 위한 과거의 연구는 대부분 단일 생체지표를 이용하는 것이었지만 이러한 방법에는 한계성이 존재한다. 따라서 본 연구에서는 생화학적 생체지표인 뇌척수액 내의 ${\alpha}-synuclein$ 단백질 수치와 영상학적 생체지표인 확산 텐서 영상의 여러 모수들을 결합한 융합 생체지표를 특징으로 사용하는 파킨슨병 진단 모델을 개발하고 성능을 평가하였다. 10-fold cross validation 에서 모든 성능지표에 대해 최고 100%를 보였으며, cross validation 의 과적합을 감안하더라도 파킨슨병의 조기진단에 유용하게 사용될 수 있는 가능성을 제시하였다.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.10
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• pp.421-428
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• 2014

Like Alzheimer's disease, Parkinson's Disease(PD) is one of the most common neurodegenerative brain disorders. PD results from the deterioration of dopaminergic neurons in the brain region called the substantia nigra. Currently there is no cure for PD, but diagnosing in its early stage is important to provide treatments for relieving the symptoms and maintaining quality of life. Unlike many diagnosis methods of PD which use a single biomarker, we developed a diagnosis method that uses both biochemical biomarkers and imaging biomarkers. Our method uses ${\alpha}$-synuclein protein levels in the cerebrospinal fluid and diffusion tensor images(DTI). It achieved an accuracy over 91.3% in the 10-fold cross validation, and the best accuracy of 72% in an independent testing, which suggests a possibility for early detection of PD. We also analyzed the characteristics of the brain fiber pathways of Parkinson's disease patients and normal elderly people.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.1
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• pp.43-50
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• 2008