Registration of dynamic contrast-enhanced MRI using a progressive principal component registration (PPCR)
Registration of dynamic contrast-enhanced MRI using a progressive principal component registration (PPCR)
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DOI：
10.1088/0031-9155/52/17/003
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发表时间：
2007-09-07
影响因子：
3.5
通讯作者：
Hawkes, D.
中科院分区：
文献类型：
--
作者：
Melbourne, A.;Atkinson, D.;Hawkes, D.
软组织动态对比增强磁共振图像（DCE-MRI）的配准是一个难点。依赖于信息内容的常规配准成本函数受到变化的强度分布的损害，导致配准不良。我们提出了一个新的数据驱动的模型，从主成分分析（PCA）的时间序列数据形成的摄取模式，避免了需要一个生理模型。我们称这个过程为渐进主成分配准（PPCR）。对使用当前最佳配准的时间序列数据的主成分生成的目标图像的人工时间序列重复执行配准。其目的是产生一个数据集，已删除随机运动伪影，但长期的对比度增强隐式保留。该程序在22个肝脏DCE-MRI数据集上进行了测试。图像的初步评估由专家观察者与序列中第一个图像的配准进行比较。在存在偏好的所有情况下，PPCR是优选的。该方法既不需要分割，也不需要药代动力学摄取模型，并且可以允许在存在对比度增强的情况下成功配准。
Registration of dynamic contrast-enhanced magnetic resonance images (DCE-MRI) of soft tissue is difficult. Conventional registration cost functions that depend on information content are compromised by the changing intensity profile, leading to misregistration. We present a new data-driven model of uptake patterns formed from a principal components analysis (PCA) of time-series data, avoiding the need for a physiological model. We term this process progressive principal component registration (PPCR). Registration is performed repeatedly to an artificial time series of target images generated using the principal components of the current best-registered time-series data. The aim is to produce a dataset that has had random motion artefacts removed but long-term contrast enhancement implicitly preserved. The procedure is tested on 22 DCE-MRI datasets of the liver. Preliminary assessment of the images is by expert observer comparison with registration to the first image in the sequence. The PPCR is preferred in all cases where a preference exists. The method requires neither segmentation nor a pharmacokinetic uptake model and can allow successful registration in the presence of contrast enhancement.