• Title/Summary/Keyword: Brain Model

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Structural Equation Modeling on Living and Brain Death Organ Donation Intention in Nursing Students (간호대학생의 생존 시와 뇌사 시 장기기증 의도에 관한 구조모형)

  • Kim, Eun A;Choi, So Eun
    • Journal of Korean Academy of Nursing
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    • v.45 no.6
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    • pp.802-811
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    • 2015
  • Purpose: The purpose of this study was to test and validate a model to predict living and brain death organ donation intention in nursing students. The conceptual model was based on the theory planned behavior. Methods: Quota sampling methodology was used to recruit 921 nursing students from all over the country and data collection was done from October 1 to December 20, 2013. Results: The model fit indices for the hypothetical model were suitable for the recommended level. Knowledge, attitude, subjective norm and perceived behavioral control explained 40.2% and 40.1% respectively for both living and brain death organ donation intention. Subjective norm was the most direct influential factor for organ donation intention. Knowledge had significant direct effect on attitude and indirect effect on subjective norm and perceived behavioral control. These effects were higher in brain death organ donation intention than in living donation intention. Conclusion: The overall findings of this study suggest the need to develop systematic education programs to increases knowledge about brain death organ donation. The development, application, and evaluation of intervention programs are required to improve subjective norm.

Brain Extraction of MR Images

  • Du, Ruoyu;Lee, Hyo Jong
    • Annual Conference of KIPS
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    • 2010.04a
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    • pp.455-458
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    • 2010
  • Extracting the brain from magnetic resonance imaging head scans is an essential preprocessing step of which the accuracy greatly affects subsequent image analysis. The currently popular Brain Extraction Tool produces a brain mask which may be too smooth for practical use to reduce the accuracy. This paper presents a novel and indirect brain extraction method based on non-brain tissue segmentation. Based on ITK, the proposed method allows a non-brain contour by using region growing to match with the original image naturally and extract the brain tissue. Experiments on two set of MRI data and 2D brain image in horizontal plane and 3D brain model indicate successful extraction of brain tissue from a head.

Comparisons of Discriminant Analysis Model and Generalized Logit Model in Stroke Patten Identifications Classification (중풍변증분류에 사용되는 판별분석모형과 일반화로짓모형의 비교)

  • Kang, Byoung-Kab;Lee, Ju-Ah;Ko, Mi-Mi;Moon, Tae-Woong;Bang, Ok-Sun
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.25 no.2
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    • pp.318-321
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    • 2011
  • In this study, when a physician make a diagnosis of the Pattern Identifications(PIs) of stroke patients, the development methods of the PIs classification function is considered by diagnostic questionnaire of the PIs for stroke patients. Clinical data collected from 1,502 stroke patients who was identically diagnosed for the PIs subtypes diagnosed by two clinical experts with more than 3 years experiences in 13 oriental medical hospitals. In order to develop the classification function into PIs using the 44 items-Fire&heat(19), Qi-deficiency(11), Yin-deficiency(7), Dampness phlegm(7)- of them was significant statistically by univariate analysis in 61 questionnaires totally, we make some comparisons of the results of discriminant analysis model and generalized logit model. The overall diagnostic accuracy rate of the PIs subtypes for discriminant model(74.37%) was higher than 3% of generalized logit model(70.09%).

Semi-automated Approach to Hippocampus Segmentation Using Snake from Brain MRI

  • Al Shidaifat, Ala'a Ddin;Al-Shdefat, Ramadan;Choi, Heung-Kook
    • Journal of Korea Multimedia Society
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    • v.17 no.5
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    • pp.566-572
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    • 2014
  • The hippocampus has been known as one of the most important structure related to many neurological disorders, such as Alzheimer's disease. This paper presents the snake model to segment hippocampus from brain MRI. The snake model or active contour model is widely used in medical image processing fields, especially image segmentation they look onto nearby edge, localizing them accurately. We applied a snake model on brain MRI. Then we compared our results with an active shape approach. The results show that hippocampus was successfully segmented by the snake model.

An analysis of the Child Head Impact Injury with Finite Element Model (유한 요소 모형을 이용한 어린이의 머리 충격 부상에 관한 연구)

  • 김영은;남대훈;왕규창
    • Journal of the Korean Society of Safety
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    • v.12 no.4
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    • pp.169-179
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    • 1997
  • The dynamic response of the human brain to direct impact was studied by three-dimensional finite element modeling. The model includes a layered shell closely representing the cranial bones with the interior contents occupied by an incompressible continuum to simulate the brain. Falx and tentorium modeled with 4 node membrane element were also incorporated. The computed pressure-time histories at 4 locations within the brain element compared quite favorably with previously published experimental data from cadaver experiments. Therefore, the purpose of this study was to determine the effects of the impact direction on the dynamic response of the brain in children. A parametric study was subsequently conducted to identify the model response when the age and impact site were varied.

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Blood-Brain Barrier Disruption in Mild Traumatic Brain Injury Patients with Post-Concussion Syndrome: Evaluation with Region-Based Quantification of Dynamic Contrast-Enhanced MR Imaging Parameters Using Automatic Whole-Brain Segmentation

  • Heera Yoen;Roh-Eul Yoo;Seung Hong Choi;Eunkyung Kim;Byung-Mo Oh;Dongjin Yang;Inpyeong Hwang;Koung Mi Kang;Tae Jin Yun;Ji-hoon Kim;Chul-Ho Sohn
    • Korean Journal of Radiology
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    • v.22 no.1
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    • pp.118-130
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    • 2021
  • Objective: This study aimed to investigate the blood-brain barrier (BBB) disruption in mild traumatic brain injury (mTBI) patients with post-concussion syndrome (PCS) using dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging and automatic whole brain segmentation. Materials and Methods: Forty-two consecutive mTBI patients with PCS who had undergone post-traumatic MR imaging, including DCE MR imaging, between October 2016 and April 2018, and 29 controls with DCE MR imaging were included in this retrospective study. After performing three-dimensional T1-based brain segmentation with FreeSurfer software (Laboratory for Computational Neuroimaging), the mean Ktrans and vp from DCE MR imaging (derived using the Patlak model and extended Tofts and Kermode model) were analyzed in the bilateral cerebral/cerebellar cortex, bilateral cerebral/cerebellar white matter (WM), and brainstem. Ktrans values of the mTBI patients and controls were calculated using both models to identify the model that better reflected the increased permeability owing to mTBI (tendency toward higher Ktrans values in mTBI patients than in controls). The Mann-Whitney U test and Spearman rank correlation test were performed to compare the mean Ktrans and vp between the two groups and correlate Ktrans and vp with neuropsychological tests for mTBI patients. Results: Increased permeability owing to mTBI was observed in the Patlak model but not in the extended Tofts and Kermode model. In the Patlak model, the mean Ktrans in the bilateral cerebral cortex was significantly higher in mTBI patients than in controls (p = 0.042). The mean vp values in the bilateral cerebellar WM and brainstem were significantly lower in mTBI patients than in controls (p = 0.009 and p = 0.011, respectively). The mean Ktrans of the bilateral cerebral cortex was significantly higher in patients with atypical performance in the auditory continuous performance test (commission errors) than in average or good performers (p = 0.041). Conclusion: BBB disruption, as reflected by the increased Ktrans and decreased vp values from the Patlak model, was observed throughout the bilateral cerebral cortex, bilateral cerebellar WM, and brainstem in mTBI patients with PCS.

Past, Present, and Future of Brain Organoid Technology

  • Koo, Bonsang;Choi, Baekgyu;Park, Hoewon;Yoon, Ki-Jun
    • Molecules and Cells
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    • v.42 no.9
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    • pp.617-627
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    • 2019
  • Brain organoids are an exciting new technology with the potential to significantly change our understanding of the development and disorders of the human brain. With step-by-step differentiation protocols, three-dimensional neural tissues are self-organized from pluripotent stem cells, and recapitulate the major millstones of human brain development in vitro. Recent studies have shown that brain organoids can mimic the spatiotemporal dynamicity of neurogenesis, the formation of regional neural circuitry, and the integration of glial cells into a neural network. This suggests that brain organoids could serve as a representative model system to study the human brain. In this review, we will overview the development of brain organoid technology, its current progress and applications, and future prospects of this technology.

Active Contour Model Based Object Contour Detection Using Genetic Algorithm with Wavelet Based Image Preprocessing

  • Mun, Kyeong-Jun;Kang, Hyeon-Tae;Lee, Hwa-Seok;Yoon, Yoo-Sool;Lee, Chang-Moon;Park, June-Ho
    • International Journal of Control, Automation, and Systems
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    • v.2 no.1
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    • pp.100-106
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    • 2004
  • In this paper, we present a novel, rapid approach for the detection of brain tumors and deformity boundaries in medical images using a genetic algorithm with wavelet based preprocessing. The contour detection problem is formulated as an optimization process that seeks the contour of the object in a manner of minimizing an energy function based on an active contour model. The brain tumor segmentation contour, however, cannot be detected in case that a higher gradient intensity exists other than the interested brain tumor and deformities. Our method for discerning brain tumors and deformities from unwanted adjacent tissues is proposed. The proposed method can be used in medical image analysis because the exact contour of the brain tumor and deformities is followed by precise diagnosis of the deformities.

Development and Degeneration of Retinal Ganglion Cell Axons in Xenopus tropicalis

  • Choi, Boyoon;Kim, Hyeyoung;Jang, Jungim;Park, Sihyeon;Jung, Hosung
    • Molecules and Cells
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    • v.45 no.11
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    • pp.846-854
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    • 2022
  • Neurons make long-distance connections via their axons, and the accuracy and stability of these connections are crucial for brain function. Research using various animal models showed that the molecular and cellular mechanisms underlying the assembly and maintenance of neuronal circuitry are highly conserved in vertebrates. Therefore, to gain a deeper understanding of brain development and maintenance, an efficient vertebrate model is required, where the axons of a defined neuronal cell type can be genetically manipulated and selectively visualized in vivo. Placental mammals pose an experimental challenge, as time-consuming breeding of genetically modified animals is required due to their in utero development. Xenopus laevis, the most commonly used amphibian model, offers comparative advantages, since their embryos ex utero during which embryological manipulations can be performed. However, the tetraploidy of the X. laevis genome makes them not ideal for genetic studies. Here, we use Xenopus tropicalis, a diploid amphibian species, to visualize axonal pathfinding and degeneration of a single central nervous system neuronal cell type, the retinal ganglion cell (RGC). First, we show that RGC axons follow the developmental trajectory previously described in X. laevis with a slightly different timeline. Second, we demonstrate that co-electroporation of DNA and/or oligonucleotides enables the visualization of gene function-altered RGC axons in an intact brain. Finally, using this method, we show that the axon-autonomous, Sarm1-dependent axon destruction program operates in X. tropicalis. Taken together, the present study demonstrates that the visual system of X. tropicalis is a highly efficient model to identify new molecular mechanisms underlying axon guidance and survival.

Fabrication of a Brain Model using the Adaptive Slicing Technique (적응단면기법을 이용한 뇌모형제작)

  • Yeom, Sang-Won;Um, Tai-Joon;Joo, Yung-Chul;Kim, Seung-Woo;Kong, Yong-Hae;Chun, In-Gook;Bang, Jae-Chul
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.4
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    • pp.485-490
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    • 2003
  • RP(Rapid Prototyping) has been used in the various industrial applications. This paper presents the optimization techniques fur fabricated 3D model design using RP machine for the medical field. Once the original brain model data are obtained from 2D slices of MRI/CT machine, the data can be modeled as an optimal ellipse. The objective of this study includes optimization of fabrication time and surface roughness using the adaptive slicing method. It can reduce fabrication time without losing surface roughness quality by accumulating the slices with variable thickness. According to the parameter tuning and synthesis of its effect, more suitable parameter values can be obtained by enhanced 3D brain model fabrication. Therefore, accurate 3D brain model fabricated by RP machine can enable a surgeon to perform pre-operation. to make a decision for the operation sequence and to perceive the 3D positions in prototype, before delicate operation of actual surgery.