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arXiv 1507.01035physics.med-ph
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磁共振成像中的信号改善和对比度增强

Signal Improvement and Contrast Enhancement in Magnetic Resonance Imaging

Yi Han

摘要:

本论文报告了磁共振成像(MRI)的进展,其最终目标是改善信号和对比度在生物医学应用中的应用。更具体地说,新的MRI脉冲序列已被设计成表征微观结构,增强组织中的信号和对比度,以及成像功能过程。本论文利用分子间多重量子相干性(iMQCs)在中间分离的自旋之间采集了大鼠脑和红骨髓的图像。作为一个重要的应用,不同方向的iMQCs图像可用于各向异性映射和组织微结构分析。同时,模拟证明了来自整体形状的偶极场对实验iMQC信号的贡献很小。除了iMQCs的幅度外,还应研究iMQCs的相位。利用该方法建立的相位各向异性图可以清晰地显示大鼠脑内的磁化率信息。它可以提供有意义的诊断信息。为了深入研究磁化率,提出了修正的银纹序列。将修正银纹图像的相位数据和iMQCs图像的相位数据相结合,非常有希望构建微结构图。显然,所有上述技术中的相位图像都需要高对比度和清晰。为了实现这一目标,来自磁化率加权成像(SWI)和磁化率张量成像(STI)的算法工具在我们的系统中非常有用和具有创造性。

英文摘要:

This thesis reports advances in magnetic resonance imaging (MRI), with the ultimate goal of improving signal and contrast in biomedical applications. More specifically, novel MRI pulse sequences have been designed to characterize microstructure, enhance signal and contrast in tissue, and image functional processes. In this thesis, rat brain and red bone marrow images are acquired using iMQCs (intermolecular multiple quantum coherences) between intermediate separated spins. As an important application, iMQCs images in different directions can be used for anisotropy mapping and tissue microstructure analysis. At the same time, the simulations prove that the dipolar field from the overall shape only has small contributions to the experimental iMQC signal. Besides magnitude of iMQCs, phase of iMQCs should be studied as well. The phase anisotropy maps built by our method can clearly show susceptibility information in rat brain. It may provide meaningful diagnostic information. To deeply study susceptibility, the modified-crazed sequence is developed. Combining phase data of modified-crazed images and phase data of iMQCs images is very promising to construct microstructure maps. Obviously, the phase image in all above techniques needs to be highly-contrasted and clear. To achieve the goal, algorithm tools from Susceptibility-Weighted Imaging (SWI) and Susceptibility Tensor Imaging (STI) stands out superb useful and creative in our system.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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