LONGITUDINAL INTENSITY NORMALIZATION IN THE PRESENCE OF MULTIPLE SCLEROSIS LESIONS.
LONGITUDINAL INTENSITY NORMALIZATION IN THE PRESENCE OF MULTIPLE SCLEROSIS LESIONS.
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DOI：
10.1109/isbi.2013.6556791
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Prince JL
中科院分区：
文献类型：
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作者：
Roy S;Carass A;Shiee N;Pham DL;Calabresi P;Reich D;Prince JL
本文提出了一种纵向强度归一化算法的T1加权磁共振图像的人脑多发性硬化病变的存在下，旨在稳定和一致的纵向分割。与以前的纵向分割方法不同，我们提出了一个4D强度归一化，可以用作任何分割方法的预处理步骤。基于一阶自回归模型，将由多发性硬化病变的复发和缓解性质引起的强度的可变性建模为否则平滑的强度变换，从而导致正常组织的分割统计的平滑变化，同时保持病变信息不受影响。我们验证了我们的方法在模拟和真实的纵向正常受试者和多发性硬化症受试者。
This paper proposes a longitudinal intensity normalization algorithm for T1-weighted magnetic resonance images of human brains in the presence of multiple sclerosis lesions, aiming towards stable and consistent longitudinal segmentations. Unlike previous longitudinal segmentation methods, we propose a 4D intensity normalization that can be used as a preprocessing step to any segmentation method. The variability in intensities arising from the relapsing and remitting nature of the multiple sclerosis lesions is modeled into an otherwise smooth intensity transform based on first order autoregressive models, resulting in smooth changes in segmentation statistics of normal tissues, while keeping the lesion information unaffected. We validated our method on both simulated and real longitudinal normal subjects and on multiple sclerosis subjects.