• Title/Summary/Keyword: MRI 영상

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The functional imaging to Diagnose Acute Cerebral infarction Comparing between CT Perfusion and MR Diffusion Imaging (급성 뇌경색 진단을 위한 CT관류영상과 MR확산영상의 비교)

  • Kim, Seon-Hee;Eun, Sung-Jong;Rim, Chae-Pyeong
    • Journal of the Korean Society of Radiology
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    • v.6 no.1
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    • pp.19-26
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    • 2012
  • It is very important for early diagnosis and therapy with ischamic cerebral infarction patients. This study was to know the ischemic penumbra lesion which compared CT-perfusion and diffusion weighted MRI(DWMRI) with acute cerebral infarction patients. 12 acute cerebral infarction patients had performed perfusion CT and performed DWMRI. Perfusion images including cerebral blood volume(CBV), cerebral blood flow(CBF), time to peak(TTP) and mean transit time(MTT) maps obtained the values with defect lesion and contralateral normal cerebral hemisphere and DWMRI was measured by signal intensity and compared of lesion size between each perfusion map. All perfusion CT maps showed the perfusion defect lesions in all patients. There were remarkable TTP and MTT delay in perfusion defect lesions. The lesions on CBF map was the most closely correlated with the lesions on DWMRI. The size of perfusion defect lesions on TTP and MTT map was larger than that of lesions on DWMRI, suggesting that MTT map can evaluate the ischemic penumbra. Perfusion CT maps make it possible to evaluate not only ischemic core and ischemic penumbra, but also hemodynamic status in the perfusion defect area. These results demonstrate that perfusion CT can be useful to the diagnosis and treatment in the patients with acute cerebral ischemic infarction.

Evaluation of the Noise Power Spectrum by Using American College of Radiology Phantom for Magnetic Resonance Imaging (자기공명영상에서 ACR 팬텀을 이용한 잡음전력스펙트럼 평가)

  • Jung-Whan Min;Hoi-Woun Jeong
    • Journal of radiological science and technology
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    • v.47 no.1
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    • pp.21-28
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    • 2024
  • This study was purpose to quantitative evaluation of comparison of the image intensity uniformity and noise power spectrum (NPS) by using American college of radiology (ACR) phantom for magnetic resonance imaging (MRI). The MRI was used achiva 3.0T MRI and discovery MR 750, 3.0T, the head and neck matrix shim SENSE head coil were 32 channels receive MR coil. The MRI was used parameters of image sequence for ACR standard and general hospital. NPS value of the ACR standard T2 vertical image in GE equipment was 7.65E-06 when the frequency was 1.0 mm-1. And the NPS value of the ACR hospital T1 region of interest (ROI) 9 over all vertical image in Philips equipment was 9E-08 when the frequency was 1.0 mm-1 and the NPS value of the hospital T2 ROI 9 over all vertical image in Philips equipment was 1.06E-07 when the frequency was 1.0 mm-1. NPS was used efficiently by using a general hospital vertical sequence more than the standard vertical sequence method by using the ACR phantom. Furthermore NPS was the quantitative quality assurance (QA) assessment method for noise and image intensity uniformity characteristics was applied mutatis mutandis, and the results values of the physical imaging NPS of the 3.0T MRI and ACR phantom were presented.

Evaluation of Quantitative Effectiveness of MR-DTI Analysis with and without Functional MRI (기능적 자기공명영상 사용유무에 따른 확산텐서영상 분석의 유효성 평가)

  • Lee, Dong-Hoon;Park, Ji-Won;Hong, Cheol-Pyo
    • The Journal of Korean Physical Therapy
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    • v.25 no.5
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    • pp.260-265
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    • 2013
  • Purpose: This study was conducted in order to evaluate the quantitative effectiveness of region of interest (ROI) setting in MR-DTI analysis with and without fMRI activation results. Methods: Ten right-handed normal volunteers participated in this study. DTI and fMRI datasets for each subject were obtained using a 1.5T MRI system. For neural fiber tracking, ROIs were drawn using two methods: The drawing points were located in the fMRI activation areas or areas randomly selected by users. In this study, the neural fiber tract targeted the corticospinal tract (CST) Quantitative analyses were performed and compared. The pixel numbers passing through the fiber tract in the individual brain volume were counted. The ratios between the ROI pixel numbers and the extracted fiber pixel numbers, and the ratios between the fiber pixel numbers and the whole-brain pixel numbers were also calculated. Results: According to our results, extracted CST fiber tract in which the ROI was drawn with fMRI activation areas showed higher distribution than drawing the ROI by users' hands. In addition, the quantitatively measured values represented higher pixel distribution: The counted average pixel numbers were 4553.8 and 1943.3. The average ratios of the ROI areas were 33.87 and 22.52. The average percentages of the individual whole-brain volume numbers were 2.06 and 0.87. Conclusion: Results of this study appear to indicate that use of this method can allow for more objectives and significant for study of the recovery of neural fiber mechanisms and brain rehabilitation.

Magnetic resonance imaging-based temporomandibular joint space evaluation in tempormandibular disorders (측두하악관절증에서 자기공명영상을 이용한 측두하악관절의 관절강 평가)

  • Nah, Kyung-Soo
    • Imaging Science in Dentistry
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    • v.37 no.1
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    • pp.15-18
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    • 2007
  • Purpose : Disc and condylar position were observed on MRIs of temporomandibular joint disorder patients and condylar position agreement between MRI and tranascranal radiography was evaluated. Materials and Methods MRI and transcranial radiographs of both TM joints from 67 patients with temporemandibular disorder were used. On MRI, the position and shape of disc and condylar position as anterior, middle, posterior was evaluated at medial, center, and lateral views. On transcranial radiographs, condylar position was evaluated using the shortest distance from condyle to fossa in anterior, superior, and posterior directions. Results. 1. On MRI, 96 joints (71.6%) of 134 had anterior disc dispalcement with reduction and 38 joints (28.4%) without reduction. 2. Fourteen (14.6%) of 96 reducible joints showed anterior condylar position, 19 (19.8%) showed central position, 63 joints (65.6%) showed posterior position. Two joints (5.3%) of 38 non-reducible joints showed anterior condylar position, while 9 (23.7%) showed central position, and 27 (71.1%)-posterior position. 3. In 85 joints (63.4%) of 134, the transcranial condylar position agreed with that of the central MRI view, 10 joints (7.5%) with that of medial, 16 joints (11.9%) with that of lateral, and 23 joints (17.2%) disagreed with that of MRI. Conclusion : On MRT, most oi the reducible and non-reducible joints showed posterior condylar position. Transcranial radiographs taken with machine designed for TMJ had better agreement of condylar position with that of MRI. Extremely narrow joint spaces or very posterior condylar positions observed on transcranial radiographs had a little more than fifty percent agreement with those of MRIs.

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Deep Multimodal MRI Fusion Model for Brain Tumor Grading (뇌 종양 등급 분류를 위한 심층 멀티모달 MRI 통합 모델)

  • Na, In-ye;Park, Hyunjin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.416-418
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    • 2022
  • Glioma is a type of brain tumor that occurs in glial cells and is classified into two types: high hrade hlioma with a poor prognosis and low grade glioma. Magnetic resonance imaging (MRI) as a non-invasive method is widely used in glioma diagnosis research. Studies to obtain complementary information by combining multiple modalities to overcome the incomplete information limitation of single modality are being conducted. In this study, we developed a 3D CNN-based model that applied input-level fusion to MRI of four modalities (T1, T1Gd, T2, T2-FLAIR). The trained model showed classification performance of 0.8926 accuracy, 0.9688 sensitivity, 0.6400 specificity, and 0.9467 AUC on the validation data. Through this, it was confirmed that the grade of glioma was effectively classified by learning the internal relationship between various modalities.

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Classification of Brain MR Images Using Spatial Information (공간정보를 이용한 뇌 자기공명영상 분류)

  • Kim, Hyung-Il;Kim, Yong-Uk;Kim, Jun-Tae
    • Journal of the Korea Society for Simulation
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    • v.18 no.4
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    • pp.197-206
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    • 2009
  • The medical information system is an effective medical diagnosis assistance system which offers an environment in which medial images and diagnosis information can be shared. However, this system can only stored and transmitted information without other functions. To resolve this problem and to enhance the efficiency of diagnostic activities, a medical image classification and retrieval system is necessary. The medical image classification and retrieval system can improve efficiency in a medical diagnosis by providing disease-related images and can be useful in various medical practices by checking diverse cases. However, it is difficult to understand the meanings contained in images because the existing image classification and retrieval system has handled superficial information only. Therefore, a medical image classification system which can classify medical images by analyzing the relation among the elements of the image as well as the superficial information has been required. In this paper, we propose the method for learning and classification of brain MRI, in which the superficial information as well as the spatial information extracted from images are used. The superficial information of images, which is color, shape, etc., is called low-level image information and the logical information of the image is called high-level image information. In extracting both low-level and high-level image information in this paper, the anatomical names and structure of the brain have been used. The low-level information is used to give an anatomical name in brain images and the high-level image information is extracted by analyzing the relation among the anatomical parts. Each information is used in learning and classification. In an experiment, the MRI of the brain including disease have been used.

Compressed Sensing Based Dynamic MR Imaging: A Short Survey (Compressed Sensing 기법을 이용한 Dynamic MR Imaging)

  • Jung, Hong;Ye, Jong-Chul
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.5
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    • pp.25-31
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    • 2009
  • The recently developed sampling theory, "compressed sensing" is gathering huge interest in MR reconstruction area because of its feasibility of high spatio-temporal resolution of dynamic MRI which has been limited in conventional methods based on Nyquist sampling theory. Since dynamic MRI usually has high redundant information along temporal direction, this can be very sparsely represented in most of cases. Therefore, compressed sensing that exploits the sparsity of unknown images can be effectively applied in most of dynamic MRI. This review article briefly introduces currently proposed compressed sensing based dynamic MR imaging algorithms and other methods exploiting sparsity. By comparing them with conventional methods, you may have insight how the compressed sensing based methods can impact nearly every area of clinical dynamic MRI.

Active Noise Control for Target Point Inside Bore Using Property of MRI Noise (MRI 소음의 특성을 이용한 공동 내부 목표점의 능동소음 제어)

  • Lee, Nokhaeng;Park, Youngjin;Park, Youn-Sik
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.24 no.1
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    • pp.62-68
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    • 2014
  • Recently, MRI(magnetic resonance imager) scanner is continually used for medical diagnosis and many biomedical researches. When it operates, however, intense noise is generated. The SPL(sound pressure level) of the noise approaches 130 dB especially in 3 T(Tesla) MRI. Meanwhile, more than 3 T MRI scanners have been developed to get higher-resolution images, so louder noise is expected in the future. The intense noise makes patients feel nervous and uncomfortable. Moreover, it could possibly cause hearing loss to patient in extreme cases. For this reason, some active noise control systems have been researched. One of them used feedback Filtered-X LMS(FXLMS) algorithm which is able to control only narrowband noises and possible to diverge in severe case. In this paper, we determine the property of MRI noise. Using the property, we applied a method of open-loop and adaptive control for reducing MRI noise at target point inside bore. We verified performance of the method with computer simulation and preliminary experiment. The results demonstrate that the method can effectively reduce MRI noise at target point.