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引用次数: 0

摘要

磁共振成像是一种新的定量磁共振成像技术,可以提供快速和同时测量多种组织特性。与快速的数据采集相比,利用MRF提取组织属性的后处理相对较慢,并且通常需要大的内存来存储图像数据集和MRF字典。本研究开发了一种卷积神经网络,可以在0.1秒内快速估计多种组织特性,白质和灰质的T1和T2值与模式匹配的结果也很吻合。
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Quantification of relaxation times in MR Fingerprinting using deep learning.

MRF is a new quantitative MR imaging technique, which can provide rapid and simultaneous measurement of multiple tissue properties. Compared to the fast speed for data acquisition, the post-processing to extract tissue properties with MRF is relatively slow and often requires a large memory for the storage of both image dataset and MRF dictionary. In this study, a convolutional neural network was developed, which can provide rapid estimation of multiple tissue properties in 0.1 sec. The T1 and T2 values obtained in white matter and gray matter are also in a good agreement with the results from pattern matching.

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