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用于扩散磁共振成像的多纤维重建算法

Multiple-fiber reconstruction algorithms for diffusion MRI.

作者信息

Alexander Daniel C

机构信息

Department of Computer Science, University College London, Gower Street, London WC1E 6BT, United Kingdom.

出版信息

Ann N Y Acad Sci. 2005 Dec;1064:113-33. doi: 10.1196/annals.1340.018.

Abstract

This chapter reviews multiple-fiber reconstruction algorithms for diffusion magnetic resonance imaging (MRI) and provides some initial comparative results for two such algorithms, q-ball imaging and PASMRI, on data from a typical clinical diffusion MRI acquisition. The chapter highlights the problems with standard approaches, such as diffusion-tensor MRI, to motivate a recent set of alternative approaches. The review concentrates on the software implementation of the new techniques. Results of the preliminary comparison show that PASMRI recovers the principal directions of simple test functions more consistently than q-ball imaging and produces qualitatively better results on the test data set. Further simulations suggest that a moderate increase in data quality allows q-ball, which is much faster to run, to recover directions with consistency comparable to that of PASMRI on the test data.

摘要

本章回顾了用于扩散磁共振成像(MRI)的多纤维重建算法,并给出了两种此类算法——q球成像和PASMRI,在典型临床扩散MRI采集数据上的一些初步对比结果。本章强调了标准方法(如扩散张量MRI)存在的问题,以推动近期一系列替代方法的发展。综述集中在这些新技术的软件实现上。初步对比结果表明,与q球成像相比,PASMRI在恢复简单测试函数的主方向上更具一致性,并且在测试数据集上产生的定性结果更好。进一步的模拟表明,数据质量的适度提高能使运行速度快得多的q球成像在测试数据上恢复出与PASMRI一致性相当的方向。

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