ENTROPY BASED DTI QUALITY CONTROL VIA REGIONAL ORIENTATION DISTRIBUTION.

ENTROPY BASED DTI QUALITY CONTROL VIA REGIONAL ORIENTATION DISTRIBUTION.
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DOI:
10.1109/isbi.2012.6235474
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发表时间:
2012
期刊:
Proceedings. IEEE International Symposium on Biomedical Imaging
影响因子:
--
通讯作者:
Styner M
Styner M
中科院分区:
其他
文献类型:
--
作者:
Farzinfar M;Dietrich C;Smith R;Li Y;Gupta A;Liu Z;Styner M

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扩散张量成像(DTI)在神经影像学领域受到越来越多的关注。然而,复杂的扩散加权图像(DWI)采集协议容易产生由运动和低信噪比(SNR)引起的伪影。一个严格的质量控制(QC)和误差校正程序是绝对必要的DTI数据分析。大多数现有的QC程序是在DWI域和/或体素水平上进行的,但我们自己的实验表明,这些方法通常不能完全检测和消除某些类型的伪影。我们提出了一个新的区域,独立的DTI-QC措施,是基于在DTI域采用熵的区域分布的主方向。这种新的QC测量旨在通过检测和纠正残留伪影来补充现有的QC程序集。实验表明,我们的自动方法可以可靠地检测和潜在地纠正这种残留的文物。结果表明,其实用性的一般质量评估的DTI研究。
Diffusion Tensor Imaging (DTI) has received increasing attention in the neuroimaging community. However, the complex Diffusion Weighted Images (DWI) acquisition protocol are prone to artifacts induced by motion and low signal-to-noise rations(SNRs). A rigorous quality control (QC) and error correction procedure is absolutely necessary for DTI data analysis. Most existing QC procedures are conducted in the DWI domain and/or on a voxel level, but our own experiments show that these methods often do not fully detect and eliminate certain types of artifacts. We propose a new regional, alignment-independent DTI-QC measure that is based in the DTI domain employing the entropy of the regional distribution of the principal directions. This new QC measurement is intended to complement the existing set of QC procedures by detecting and correcting residual artifacts. Experiments show that our automatic method can reliably detect and potentially correct such residual artifacts. The results indicate its usefulness for general quality assessment in DTI studies.
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