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Model-based intensity nonuniformity correction in brain MRI

机译:基于模型的脑部MRI强度不均匀校正

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Intensity nonuniformity is an artifact frequently observed on magnetic resonance (MR) images. It consists in anatomically irrelevant intensity variations that often lead automated segmentation algorithms to fail. This paper presents a novel approach for correcting those intensity variations. It is based on the assumption that clues about intensity nonuniformity can be found by modeling the acquisition sequence used. Thus, we develop a model from which transmitted and received B/sub 1/ fields can be computed for both homogeneous and heterogeneous objects. The proposed method has been evaluated on both physical phantom and human brain datasets using conventional quantitative criteria. The results show a significant reduction in intensity nonuniformity, especially for severe cases, and demonstrate a new wax of dealing with this type of artifacts.
机译:强度不均匀性是在磁共振(MR)图像上经常观察到的伪影。它包含解剖学上不相关的强度变化,这些变化通常会导致自动分割算法失败。本文提出了一种校正这些强度变化的新颖方法。它基于这样的假设,即可以通过对所使用的采集序列进行建模来找到有关强度不均匀性的线索。因此,我们开发了一个模型,从该模型可以计算出同质和异质对象的B / sub 1 /场。使用常规的定量标准,已在物理幻象和人脑数据集上对所提出的方法进行了评估。结果表明,强度不均匀性显着降低,尤其是在严重的情况下,并且证明了可以处理此类伪像的新型蜡。

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