• Title/Summary/Keyword: MRI Image

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Sketch query method for medical image retrieval based on disease icon (의료 영상 검색을 위한 아이콘 기반의 스케치 질의 작성 방안)

  • 이낙훈;엄기현
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.10a
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    • pp.122-124
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    • 2000
  • 본 논문은 질병이 있는 뇌종양 MRI 이미지 검색을 위해 아이콘 기반의 스케치 질의 방안을 제시한다. 기존의 이미지 검색 시스템은 이미지가 갖는 속성 중 일부의 속성 값만을 가지고 사용자가 직접 질의 이미지를 작성한다. 그러나 이런 방법으로는 여러 복잡한 속성값을 갖는 뇌종양 MRI 이미지의 내용을 표현하기는 어렵다. 그래서 본 논문에서는 질병이 있는 뇌 MRI 이미지 검색을 위해 아이콘을 사용한 템플릿 형식의 메디컬 스케치 질의 방법을 제시한다. 뇌에서 발생하는 뇌질환을 질병별로 분류하였고, 분류된 질병들이 가지고 있는 색상이나 질감, 모양과 같은 속성 값들을 아이콘화하여 템플릿 이미지로 제공되는 정상인의 이미지에 정의된 질병 아이콘의 크기와 위치를 설정함으로써 사용자가 검색하고자 하는 질의 이미지를 쉽게 작성할 수 있는 스케치 형식의 질의방법을 제안한다.

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Understanding of Perfusion MR Imaging (관류자기공명영상의 이해)

  • Goo, Eun-Hoe
    • Korean Journal of Digital Imaging in Medicine
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    • v.15 no.1
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    • pp.27-31
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    • 2013
  • Perfusion MR imaging is how to use exogenous and endogenous contrast agent. Exogenous perfusion MRI methods which are dynamic susceptibility contrast using $T2^*$ effect and dynamic contrast-enhanced using T1 weighted image after injection contrast media. An endogenous perfusion MRI method which is arterial spin labeling using arterial blood flow in body. In order to exam perfusion MRI in human, technical access are very important according to disease conditions. For instance, dynamic susceptibility contrast is used in patients with acute stroke because of short exam time, while dynamic susceptibility contrast or dynamic contrast enhancement provides the various perfusion information for patients with tumor, vascular stenosis. Arterial spin labeling is useful for children, women who are expected to be pregnant. In this regard, perfusion MR imaging is required to understanding, and the author would like to share information with clinical users

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A novel detection method of periodically moving region in radial MRI

  • Seo, Hyunseok;Park, HyunWook
    • IEIE Transactions on Smart Processing and Computing
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    • v.2 no.4
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    • pp.203-207
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    • 2013
  • The appropriate handling of motion artifacts is essential for clinical diagnosis in magnetic resonance imaging (MRI). In many cases, motion is an inherent part of MR images because it is difficult to control during MR imaging. As the motion in the human body occur in a deformable manner, they are difficult to deal with. This paper proposes a novel detection method for periodically moving regions to produce MR images with less motion artifacts. When the data is acquired by the radial trajectory, the proposed method can extract the deformable region easily using the difference in the modulated sinograms, which have different periodic phase terms. The simulation results applied to the various cases confirmed the good performance of the proposed method.

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A study on the implementation of Imaging System for Magnetic Resonance Imaging (자기공명전단을 위한 영상화 시스템 구현에 관한 연구)

  • Jin, S.O.;Won, J.I.;Park, Y.H.;Huh, Y.;Kim, K.H.
    • Proceedings of the KIEE Conference
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    • 1998.11b
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    • pp.597-599
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    • 1998
  • The clinical acceptance of magnetic resonance imaging(MRI) system has been more rapid than that of the other medical image diagnosis system(X-ray, CT, etc) with the advantage of nonhazardous nature, high resolution capability, potential for chemically specified imaging. MRI system is composed of super conducting magnet, gradient fields, rf transceiver, system controller and imaging software technology. In this paper, introducing the principle of magnetic resonance imaging, it proposes the implementation of PC-based MRI system.

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Fundamental Background for 3T MRI/MRS

  • Choe, Bo-Young
    • Proceedings of the KSMRM Conference
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    • 2002.11a
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    • pp.47-49
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    • 2002
  • At present, the trend of magnetic field strength in MRI system is dramatically changing. In early 70, the only low field (<0.5T) was developed. It was technically difficult to develop the high field system. At that time, people believed that the fine MR imaging could not be obtained in the high field MR system due to the magnetic susceptibility effect. However, 1.5T system was evolved at the end of 80, and used for clinical usage. Thus, it was proved that the signal to noise ratio (SNR) could be greatly contribute to enhance the image quality. And, the results of functional MRI and MR spectroscopy could be improved in the higher field MR system. So, 8T system was eventually developed in Ohio State University Hospital at the end of 90. Therefore, there is no doubt that the system with the ultra high magnetic field strength will be developed near future in 21 century.

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Study on the Implementation of the Digital Controller of High-Speed PWM Current Amplifier (디지털 제어 방식의 고속 PWM 전류 증폭기의 구현에 관한 연구)

  • Ko, Deog-Hwa;Baek, Kwang-Ryul
    • Journal of Institute of Control, Robotics and Systems
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    • v.8 no.2
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    • pp.97-103
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    • 2002
  • This paper deals with a PWM(Pulse Width Modulation) current amplifier using digital controller in order to generate a gradient magnetic field far the MRI(Magnetic Resonance Image) system. Because of tolerance of discrete devices, it is difficult to set accurate values of the control parameters and to make an analog-controlling circuit. However, using digital controller, it is possible to set exact control parameters and to adopt a modern control techniques. It is shown that the digital controller will highly enhance the output current response and it will improve the quality of the MRI.

Application of Iron Related Magnetic Resonance Imaging in the Neurological Disorders (신경계 질환에서 철 관련 자기공명영상 기법의 활용)

  • Kim, Tae-Hyoung;Lee, Jae-Hyeok
    • Annals of Clinical Neurophysiology
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    • v.16 no.1
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    • pp.1-7
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    • 2014
  • Iron is an important element for brain oxygen transport, myelination, DNA synthesis and neurotransmission. However, excessive iron can generate reactive oxygen species and contribute neurotoxicity. Although brain iron deposition is the natural process with normal aging, excessive iron accumulation is also observed in various neurological disorders such as neurodegeneration with brain iron accumulation, Parkinson's disease, Alzheimer's disease, multiple sclerosis, Friedreich ataxia, and others. Magnetic resonance image (MRI) is a useful method for detecting iron deposits in the brain. It can be a powerful tool for diagnosis and monitoring, while furthering our understanding of the role of iron in the pathophysiology of a disease. In this review, we will introduce the mechanism of iron toxicity and the basics of several iron-related MRI techniques. Also, we will summarize the previous results concerning the clinical application of such MR imagings in various neurological disorders.

Volume Image Processing for Surface Based MRI-PET Registration (표면 정보 기반 MRI-PET 영상 정합을 위한 볼륨 영상 처리)

  • Jung, Myung-Jin;Choi, Yoo-Joo;Kim, Min-Jeong;Kim, Myoung-Hee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2002.11a
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    • pp.475-478
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    • 2002
  • 영상 정합이란 영상들을 배열하여 대응되는 특성을 연관시키는 과정으로, 서로 다른 정보를 결합하여 상호 보완적이고 복합적인 새로운 정보를 생성한다는 점에서 유용하다. 본 논문에서는 MRI와 PET 뇌 영상을 표면 정보에 기반하여 정합하기 위한 영상 처리 방법에 대하여 연구하였다. 특히 정합을 위한 특징점 집합을 샘플링하는데 있어서 표면 곡률 정보를 사용한 샘플링 기법을 적용하고, 실 관심 객체의 볼륨 크기에 기반한 바운딩 박스를 생성하여 기하 변환을 수행함으로써 표면정보기반 다중모달리티 영상 정합을 위한 보다 효과적인 영상 처리 결과를 얻도록 하였다.

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Brain Trouble Detection of MRI Image using Markov Random Field (마르코프 랜덤 필드를 이용한 자기 공명 영상의 뇌질환 검출)

  • 조상현;염동훈;김태형;김두영
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2003.06a
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    • pp.1-5
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    • 2003
  • 의료영상의 분할은 의료영상을 컴퓨터 진단 및 가시화에 필요한 같은 성질을 가진 여러 조직으로 나누어주는 방법이다. 즉 입력되어진 영상을 처리하여 유사한 화소들의 집합인 영역들로 화소들을 구분하는 작업이며 영상분할의 결과는 영상인식의 정확성에 큰 영향을 미친다. MRI(Magnetic Resonance Imaging)으로부터 정상적인 세포조직 또는 뇌종양과 같은 비정상적인 세포조직의 가시화와 분석을 위해서는 대상 세포조직의 적절한 분류를 필요로 한다. 하지만 기존의 영역 검출 방법으로는 잡음이 섞여 있는 영상에서 여러 가지의 처리과정(주로 잡음 제거)이 필수적이고 그런 과정으로 인해 정확한 영역 검출이 힘들게 된다. 이에 잡음이 있더라도 이를 제거하기 위한 처리가 필요 없이 영역기반으로 필요한 파라미터의 추정을 통한 MRF(Markov Random Field)를 이용하여 보다 효율적이고 정확하게 MRI에서 질환 영역을 검출할 수 있다.

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A Comparative Study of the CNN Model for AD Diagnosis

  • Vyshnavi Ramineni;Goo-Rak Kwon
    • Smart Media Journal
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    • v.12 no.7
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    • pp.52-58
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    • 2023
  • Alzheimer's disease is one type of dementia, the symptoms can be treated by detecting the disease at its early stages. Recently, many computer-aided diagnosis using magnetic resonance image(MRI) have shown a good results in the classification of AD. Taken these MRI images and feed to Free surfer software to extra the features. In consideration, using T1-weighted images and classifying using the convolution neural network (CNN) model are proposed. In this paper, taking the subjects from ADNI of subcortical and cortical features of 190 subjects. Consider the study to reduce the complexity of the model by using the single layer in the Res-Net, VGG, and Alex Net. Multi-class classification is used to classify four different stages, CN, EMCI, LMCI, AD. The following experiment shows for respective classification Res-Net, VGG, and Alex Net with the best accuracy with VGG at 96%, Res-Net, GoogLeNet and Alex Net at 91%, 93% and 89% respectively.