IEEE Trans Med Imaging. 2014 Feb;33(2):384-99. doi: 10.1109/TMI.2013.2285500. Epub 2013 Oct 11.
Validation is arguably the bottleneck in the diffusion magnetic resonance imaging (MRI) community. This paper evaluates and compares 20 algorithms for recovering the local intra-voxel fiber structure from diffusion MRI data and is based on the results of the "HARDI reconstruction challenge" organized in the context of the "ISBI 2012" conference. Evaluated methods encompass a mixture of classical techniques well known in the literature such as diffusion tensor, Q-Ball and diffusion spectrum imaging, algorithms inspired by the recent theory of compressed sensing and also brand new approaches proposed for the first time at this contest. To quantitatively compare the methods under controlled conditions, two datasets with known ground-truth were synthetically generated and two main criteria were used to evaluate the quality of the reconstructions in every voxel: correct assessment of the number of fiber populations and angular accuracy in their orientation. This comparative study investigates the behavior of every algorithm with varying experimental conditions and highlights strengths and weaknesses of each approach. This information can be useful not only for enhancing current algorithms and develop the next generation of reconstruction methods, but also to assist physicians in the choice of the most adequate technique for their studies.
验证可以说是扩散磁共振成像(MRI)领域的瓶颈。本文评估和比较了 20 种从扩散 MRI 数据中恢复局部体素内纤维结构的算法,这些算法是基于在“2012 年 ISBI”会议背景下组织的“HARDI 重建挑战赛”的结果。评估的方法包括文献中众所周知的经典技术的混合,如扩散张量、Q-球和扩散谱成像,以及受最近压缩感知理论启发的算法,以及首次在本次竞赛中提出的全新方法。为了在受控条件下定量比较这些方法,我们合成生成了两个具有已知真实值的数据集,并使用两个主要标准来评估每个体素中重建的质量:正确评估纤维群的数量和它们方向的角度精度。这项比较研究调查了每种算法在不同实验条件下的行为,并突出了每种方法的优缺点。这些信息不仅有助于增强当前的算法并开发下一代重建方法,还可以帮助医生选择最适合他们研究的技术。