Investigation of a pulsation artefact reduction technique in diffusion-weighted magnetic resonance imaging of the liver

肝脏扩散加权磁共振成像中脉动伪影减少技术的研究

基本信息

  • 批准号:
    446875476
  • 负责人:
  • 金额:
    --
  • 依托单位:
  • 依托单位国家:
    德国
  • 项目类别:
    Research Grants
  • 财政年份:
    2020
  • 资助国家:
    德国
  • 起止时间:
    2019-12-31 至 2022-12-31
  • 项目状态:
    已结题

项目摘要

One problem in magnetic resonance diffusion-weighted imaging (DWI) of the liver is the signal loss in the left liver lobe, which is caused by cardiac pulsation. The aim of this proposal is to improve the image quality of liver DWI by reducing this artefact and achieving black-blood images at the same time. For this purpose, a mixed protocol shall be used, whose feasibility for this task was proven in a recent own volunteer study. It contains a conventional bipolar diffusion encoding at a small b-value (50 s/mm²), and a flow-compensated diffusion encoding at a high b-value (800 s/mm²). This protocol shall be used in a prospective patient study including patients with known or suspected liver lesions. The visibility of the lesions in the left liver lobe is one of the key parameters that shall be evaluated. To achieve a further improvement of the image quality, advanced postprocessing schemes shall be developed and evaluated. They comprise conventional approaches featuring e.g. outlier detection. Moreover, convolutional neural networks shall be trained to generate high quality images from the set of the acquired diffusion-weighted images.
肝脏磁共振弥散加权成像(DWI)中的一个问题是左肝叶中的信号丢失,这是由心脏搏动引起的。该提案的目的是通过减少这种伪影并同时实现黑血图像来提高肝脏DWI的图像质量。 为此,应使用混合方案,其可行性已在最近的志愿者研究中得到证明。它包含小b值(50 s/mm²)时的传统双极扩散编码和高b值(800 s/mm²)时的流量补偿扩散编码。本方案应用于前瞻性患者研究,包括已知或疑似肝脏病变的患者。左肝叶病变的可见性是应评价的关键参数之一。为了进一步提高图像质量,应开发和评估高级后处理方案。它们包括以例如离群值检测为特征的常规方法。此外,卷积神经网络将被训练以从所采集的扩散加权图像的集合生成高质量图像。

项目成果

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Professor Dr. Frederik B. Laun其他文献

Professor Dr. Frederik B. Laun的其他文献

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{{ truncateString('Professor Dr. Frederik B. Laun', 18)}}的其他基金

New approaches for the determination of the structure of biological tissue using quantitative magnetic resonance imaging
使用定量磁共振成像确定生物组织结构的新方法
  • 批准号:
    430650228
  • 财政年份:
    2019
  • 资助金额:
    --
  • 项目类别:
    Heisenberg Grants
Neue Ansätze zur Strukturbestimmung biologischen Gewebes mittels der diffusionsgewichteten Magnetresonanztomographie
使用扩散加权磁共振成像确定生物组织结构的新方法
  • 批准号:
    320694886
  • 财政年份:
    2016
  • 资助金额:
    --
  • 项目类别:
    Heisenberg Professorships
New approaches for structure determination of biologic tissues by diffusion weighted magnetic resonance tomography
通过扩散加权磁共振断层扫描确定生物组织结构的新方法
  • 批准号:
    272123490
  • 财政年份:
    2015
  • 资助金额:
    --
  • 项目类别:
    Heisenberg Fellowships
NMR Based Diffusion Pore Imaging: A novel imaging concept
基于核磁共振的扩散孔隙成像:一种新颖的成像概念
  • 批准号:
    232771676
  • 财政年份:
    2013
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Auflösungsphantome und deren Anwendungen in der diffusionsgewichteten Bildgebung: Fibertracking, Kreuzungen, Anisotropien
分辨率模型及其在扩散加权成像中的应用:光纤跟踪、交叉、各向异性
  • 批准号:
    162020092
  • 财政年份:
    2010
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Diffusion-weighted imaging with flow-compensated diffusion encodings and tri-exponential IVIM imaging
具有流量补偿扩散编码和三指数 IVIM 成像的扩散加权成像
  • 批准号:
    437119659
  • 财政年份:
  • 资助金额:
    --
  • 项目类别:
    Research Grants

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