• 제목/요약/키워드: Brain imaging technique

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Acute Acquired Metabolic Encephalopathy Based on Diffusion MRI

  • Se Jeong Jeon;See Sung Choi;Ha Yon Kim;In Kyu Yu
    • Korean Journal of Radiology
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    • 제22권12호
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    • pp.2034-2051
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    • 2021
  • Metabolic encephalopathy is a critical condition that can be challenging to diagnose. Imaging provides early clues to confirm clinical suspicions and plays an important role in the diagnosis, assessment of the response to therapy, and prognosis prediction. Diffusion-weighted imaging is a sensitive technique used to evaluate metabolic encephalopathy at an early stage. Metabolic encephalopathies often involve the deep regions of the gray matter because they have high energy requirements and are susceptible to metabolic disturbances. Understanding the imaging patterns of various metabolic encephalopathies can help narrow the differential diagnosis and improve the prognosis of patients by initiating proper treatment regimen early.

Functional Magnetic Resonance Imaging with Arterial Spin Labeling: Techniques and Potential Clinical and Research Applications

  • Kim, Ju Ho;Choi, Dae Seob;Park, Sung Eun;Choi, Ho Cheol;Kim, Seong Hu
    • Investigative Magnetic Resonance Imaging
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    • 제21권2호
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    • pp.91-96
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    • 2017
  • Purpose: To describe technical methods for functional magnetic resonance imaging (fMRI) study with arterial spin labeling (ASL) compared to blood oxygenation level-dependent (BOLD) technique and discuss the potential of ASL for research and clinical practice. Materials and Methods: Task-based (n = 1) and resting-state fMRI (rs-fMRI) (n = 20) were performed using ASL and BOLD techniques. Results of both techniques were compared. Results: For task-based fMRI with finger-tapping, the primary motor cortex of the contralateral frontal lobe and the ipsilateral cerebellum were activated by both BOLD and ASL fMRI. For rs-fMRI of sensorimotor network, functional connectivity showed similar results between BOLD and ASL. Conclusion: ASL technique has potential application in clinical and research fields because all brain perfusion imaging, CBF measurement, and rs-fMRI study can be performed in a single acquisition.

뇌영상 MEG 데이터에 대한 통계적 분석 문제 (Statistical analysis issues for neuroimaging MEG data)

  • Kim, Jaehee
    • 응용통계연구
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    • 제35권1호
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    • pp.161-175
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    • 2022
  • 뇌활동으로 발생하는 전기신호는 다시 자기신호로 유도되는데 센서로 측정한 것을 뇌자도(magnetoencephalography, MEG)라고 한다. MEG 기술은 비접촉, 비침습적인 측정방법이고 시간분해능과 공간분해능력이이 우수하기 때문에 뇌의 기능적인 정보를 얻는데 유용하게 사용될 수 있다. 또한 MEG 신호를 측정하고 분석하여 뇌신경전류의 활동을 이해할 수 있고 나아가 정밀한 뇌기능 연구가 가능하다. 본 연구에서는 뇌 활동(brain activity) 현상에 관한 궁극적 정보를 얻기위해 MEG 데이터의 특성을 설명하고 통계적 문제를 다루어 앞으로 뇌연구에 통계학의 필요성과 뇌정보학의 중요성을 강조하고자 한다.

다양한 두개강내 질환의 확산강조 자기공명영상 : 임상적 유용성 (Diffusion-Weighted MR Imaging of Various Intracranial Diseases : Clinical Utility)

  • 김영준
    • Investigative Magnetic Resonance Imaging
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    • 제2권1호
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    • pp.104-112
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    • 1998
  • 목적 : 다양한 두개강내 질환을 가진 환자들을 대상으로 확산강조영상을 시행하여 병변의 신호강도를 분석함으로써 확산강조영상의 임상적 유용성을 알아보고자 하였다. 대상 및 방법 : 전향적으로 무작위 추출하여 확산강조영상을 시행한 70명의 환자(급성 뇌경색 20명, 만성 뇌경색 또는 소혈관 질환 21명, 두개강내 원발성 종양 14명, 뇌전이 3명, 뇌종양 5명, 뇌혈종 5명, 퇴행중의 유구낭미충 1명, 유피낭종 1명)를 대상으로 하였다. 확산강조영상은 1.5T 장치를 사용하여, single shot spin echo EPI 기법을 사용하여, 6500ms TR, 107ms TE, $128{\times}128$ matrix, 1 number of excitation, $24{\times}24{\;}cm$ field of view, 5-7mm slice thickness, 2-3 mm inter-slice gap으로, x, y, z 세방향으로 확산경사자기($b=1000s{\;}/{\;}textrm{mm}^2$)를 가하여 얻었다. 병변의 신호강도의 평가는 정성적인 분석에서는 병변의 신호강도를 임의의 5단계로 구분하여 분석하였고, 정량적 분석에서는 ROI(region of interest)를 이요하여 병변의 신호강도를 측정하여, 반대쪽 정상 뇌실질에서 얻은 신호강도와의 상대적 신호강도비를 구하였다. 결과 : 정성적 분석에서 매우 높은 신호강도를 보인 병변은 모든 예의 급성 뇌경색, 뇌농양, 유피낭종, 그리고 퇴행성 유구낭미충의 낭성 병변이었다. 뇌혈종은 모든 예에서 병변내에 매우 높은 신호강도와 낮은 신호강도가 혼재되어 있었다. 1명의 종양환자에서는 고형성 부분에 국소적인 매우 높은 신호강도가 보였다. 이들 병변 각각의 뇌실질에 대한 평균 신호 강도비는 모두 2.5 이상이엇다. 정성적 분석에서 죄실질과 같은 정도의 신호강도를 보인 경우는 실경교증(71%), 뇌종양의 고형성 부분(64%), 뇌전이 (100%), 혈관성 부종(67%)이었으며, 이들 병변의 뇌실질에 대한 평균 신호강도비는 1.15에서 1.28로 서로간에 의미있는 차이는 없었다.(p>0.1). 매우 낮거나 약간 낮은 신호강도를 보인 경우는 낭성 뇌연화증과 종양내 괴사로서, 평균 신호강도비는 각각 0.45와 0.42였다. 결론 : 급성 뇌경색, 뇌농양, 유피낭종, 퇴행중의 유구낭미충은 확산강조영상에서 매우 높은 신호강도를 보여, 다른 실환과의 감별 진단에 유용할 것으로 생각되며, 특히 뇌농양과 괴사나 낭성 부분을 포함한 뇌종양과의 감별에 많은 도움이 될 것으로 기대된다.

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The Output Characteristics of Transcranial Magnetic Stimulation with Voltage Variable Capacitor-Charging System

  • Kim, Whi-Young
    • Journal of information and communication convergence engineering
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    • 제8권2호
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    • pp.205-211
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    • 2010
  • In this study, a Magnetic stimulation Pulse Train control technique is introduced and applied to Flyback converter operating in discontinuous conduction mode. In contrast to the conventional pulse width modulation control scheme, the principal idea of a Magnetic stimulation Pulse Train is to achieve output voltage regulation using high and low power pulses. The proposed technique is applicable to any converter operating in discontinuous conduction. However, this work mainly focuses on Flyback topology. In this paper, the main mathematical concept of the new control algorithm is introduced and simulations as well as experimental results are presented.

Comparison of Segmentation based on Threshold and KCMeans Method

  • R.Spurgen Ratheash;M.Mohmed Sathik
    • International Journal of Computer Science & Network Security
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    • 제24권9호
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    • pp.93-96
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    • 2024
  • The segmentation, detection, and extraction of infected tumour area from magnetic resonance (MR) images are a primary concern but a tedious and time taking task performed by radiologists or clinical experts, and their accuracy depends on their experience only. So, the use of computer aided technology becomes very necessary to overcome these limitations. In this study, to improve the performance and reduce the complexity involves in the medical image segmentation process, we have investigated many algorithm methods are available in medical imaging amongst them the Threshold technique brain tumour segmentation process gives an accurate result than other methods for MR images. The proposed method compare with the K-means clustering methods, it gives a cluster of images. The experimental results of proposed technique have been evaluated and validated for performance and quality analysis on magnetic resonance brain images, based on accuracy, process time and similarity of the segmented part. The experimental results achieved more accuracy, less running time and high resolution.

Software Development for the Visualization of the Orientation of Brain Fiber Tracts in Diffusion Tensor Imaging Using a 24 bit Color Coding

  • Jung-Su Oh;In Chan Song;Ik-Hwan Cho;Jong-Hyo Kim;Kee Hyun Chang;Kwang-Suk Park
    • 대한의용생체공학회:의공학회지
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    • 제25권1호
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    • pp.43-47
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    • 2004
  • 뇌의 기능성과 분산 영역간의 연결성에 대한 관심이 매우 증대되고 있는 추세다. 그 중에서 DTI (확산 텐서 영상)는 비침습적으로 뇌에서의 물분자의 확산과 뇌의 회백질 신경 다발 구조에 대한 정보를 제공할 수 있는 자기공명영상 기법이다. 따라서 우리는 이 기법을 통해 다른 해부학적 혹은 기능적 자기공명영상 기법으로는 얼을 수 없는 뇌의 신경 섬유 다발과 대뇌 피질 영역의 연결성 정보를 얻을 수 있다. 본 연구에서는 컬러 코딩 방식에 의하여 뇌의 주된 신경 다발의 방향성을 가시화 하고자 한다. 인간 뇌의 방향성 지도는 연합섬유, 방사섬유. 교련섬유. 운동 및 감각회로 섬유의 다발들을 구별하기 쉽게 하여준다. 우리는 이 목적 하에 24비트 칼라코딩 방법을 윈도우 PC 환경에서 IDL을 이용하여 구현하였다. 덧붙여 방향성의 각각의 성분 및 이방성에 대한 컬러 코딩과 이들을 표현하기 위한 다양한 색상표를 구현하였다. 결론적으로 우리의 24 비트 킬러 코딩을 이용한 뇌 회백질의 신경 다발의 방향성 가시화에 성공하였다. 우리가 구현한 방법에 의해 뇌의 주요 신경 다발들이 잘 가시화됨을 확인하였다.

MR diagnosis of cranial neuritis focusing on facial neuritis: Performance of contrast-enhanced 3D-FLAIR technique

  • Lee, Ho Kyu;Koh, Myeong Ju;Kim, Seung Hyoung;Oh, Jung-Hwan
    • Journal of Medicine and Life Science
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    • 제16권1호
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    • pp.1-5
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    • 2019
  • Our purpose was to evaluate usefulness of the contrast-enhanced 3 dimensional fluid attenuated inversion recovery (3D-FLAIR) technique of half brain volume to diagnose the patients with facial neuritis based on segment-based analysis. We assessed retrospectively 17 consecutive patients who underwent brain MR imaging at 3 tesla for facial neuritis: 11 patients with idiopathic facial neuritis and 6 with herpes zoster oticus. Contrast enhanced 3D-FLAIR sequences of the half brain volume were analyzed and 3D T1-weighted sequence of the full brain volume were used as the base-line exam. Enhancement of the facial nerve was determined in each segment of 5 facial nerve segments by two radiologists. Sensitivity, specificity and accuracy of enhancement of each segment were assessed. The authors experienced a prompt fuzzy CSF enhancement in the fundus of the internal auditory canal in patients with enhancement of the canalicular segment. Interobserver agreement of CE 3D-FLAIR was excellent(${\kappa}$-value 0.885). Sensitivity, specificity, and accuracy of each segment are 1.0, 0.823, 0.912 in the canalicular segment; 0.118, 1.0, 0.559 in the labyrinthine segment; 0.823, 0.294, 0.559 in the anterior genu; 0.823, 0.529, 0.676 in the tympanic segment; 0.823, 0.235, 0.529 in the mastoid segment, respectively. In addition, those of prompt fuzzy enhancement were 0.647, 1.0, and 0.824, respectively. Incidence of prompt fuzzy enhancement with enhancement of the canalicular segment was 11 sites(55%): 6 (54.5%) in idiopathic facial neuritis and 5 (83.3%) in herpes zoster. Enhancement of the canalicular segment and prompt fuzzy enhancement on CE 3D-FLAIR was significantly correlated with occurrence of facial neuritis (p<0.001). CE 3D-FLAIR technique of the half brain volume is useful to evaluate the patients with facial neuritis as an adjunct sequence in addition to contrast-enhanced 3D T1-weighted sequence. On segment-based analysis, contrast enhancement of the canalicular segment is the most reliable. Prompt fuzzy enhancement is seen in not only herpes zoster, but in idiopathic facial neuritis.

CAD for Detection of Brain Tumor Using the Symmetry Contribution From MR Image Applying Unsharp Mask Filter

  • Kim, Dong-Hyun;Ye, Soo-Young
    • Transactions on Electrical and Electronic Materials
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    • 제15권4호
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    • pp.230-234
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    • 2014
  • Automatic detection of disease helps medical institutions that are introducing digital images to read images rapidly and accurately, and is thus applicable to lesion diagnosis and treatment. The aim of this study was to apply a symmetry contribution algorithm to unsharp mask filter-applied MR images and propose an analysis technique to automatically recognize brain tumor and edema. We extracted the skull region and drawed outline of the skull in database of images obtained at P University Hospital and detected an axis of symmetry with cerebral characteristics. A symmetry contribution algorithm was then applied to the images around the axis of symmetry to observe intensity changes in pixels and detect disease areas. When we did not use the unsharp mask filter, a brain tumor was detected in 60 of a total of 95 MR images. The disease detection rate for the brain was 63.16%. However, when we used the unsharp mask filter, the tumor was detected in 87 of a total of 95 MR images, with a disease detection rate of 91.58%. When the unsharp mask filter was used in the pre-process stage, the disease detection rate for the brain was higher than when it was not used. We confirmed that unsharp mask filter can be used to rapidly and accurately to read many MR images stored in a database.

THE ELEVATION OF EFFICACY IDENTIFYING PITUITARY TISSUE ABNORMALITIES WITHIN BRAIN IMAGES BY EMPLOYING MEMORY CONTRAST LEARNING TECHNIQUES

  • S. SINDHU;N. VIJAYALAKSHMI
    • Journal of applied mathematics & informatics
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    • 제42권4호
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    • pp.931-943
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    • 2024
  • Accurately identifying brain tumors is crucial for medical imaging's precise diagnosis and treatment planning. This study presents a novel approach that uses cutting-edge image processing techniques to automatically segment brain tumors. with the use of the Pyramid Network algorithm. This technique accurately and robustly delineates tumor borders in MRI images. Our strategy incorporates special algorithms that efficiently address problems such as tumor heterogeneity and size and shape fluctuations. An assessment using the RESECT Dataset confirms the validity and reliability of the method and yields promising results in terms of accuracy and computing efficiency. This method has a great deal of promise to help physicians accurately identify tumors and assess the efficacy of treatments, which could lead to higher standards of care in the field of neuro-oncology.