Challenges of imaging structure and function with MRI

Challenges of imaging structure and function with MRI
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MRI 成像结构和功能的挑战

DOI:
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发表时间:
2000
影响因子:
--
通讯作者:
Z. Liang
Z. Liang
中科院分区:
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文献类型:
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作者:
E. M. Haacke;Z. Liang

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磁共振成像(MRI)是一种基于众所周知的核磁共振(NMR)现象的层状成像技术,最早是由哈佛大学的Edward Purcell小组和斯坦福大学的Felix Bloch小组于1946年在块状材料中独立观察到的。MRI的基本概念是由Paul Lauterbur在1972年提出的。从那时起,核磁共振成像已经发展成为成像物体的首要工具,特别是对人体进行体内成像。MRI实验通常被设计成收集代表被成像对象的傅里叶变换的数据的方式。这意味着,在任何其他领域,如光学或天文学,为改进图像重建和处理而开发的任何方法,也可以在这里使用。同样,通过MRI的进步引入的新概念也可以应用于这些其他领域。要了解MR基础知识和相关重建问题的更多信息,我们建议读者参考该领域最近的三篇文章[5-7]。本文介绍了目前磁共振成像中用于组织结构和功能研究的图像重建和处理问题。在图像重建中,我们讨论了对新算法的需求,该算法可以从减少的数据量中产生具有良好信噪比的高分辨率图像。在图像处理中,我们描述了图像自动配准和分割的突出问题。
Magnetic resonance imaging (MRI) is a tomographic imaging technique based on the well-known nuclear magnetic resonance (NMR) phenomenon first observed in bulk materials independently by Edward Purcell’s group at Harvard [1] and Felix Bloch’s group at Stanford in 1946 [2]. The fundamental MRI concept was proposed by Paul Lauterbur in 1972 [3]. Since then, MRI has developed into a premier tool for imaging objects and, specifically, for imaging the human body in vivo [4]. MRI experiments are generally designed in a way to collect data that represent the Fourier transform of the object being imaged. This means that any method developed for improved image reconstruction and processing in any other field such as optics or astronomy, for example, could be used here as well. Likewise, new concepts introduced through advances in MRI may have applications to these other fields. For more information about the basics of MR and related reconstruction issues, we refer the reader to three recent texts in the field [5-7]. This article deals with current image reconstruction and processing issues in MRI for the study of tissue structure and function. In image reconstruction, we discuss the need for new algorithms that can produce high-resolution images with good signal-to-noise ratio from reduced amounts of data. In image processing, we describe outstanding problems in automatic image registration and segmentation.
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