Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations.
Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations.
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DOI：
10.1016/s1361-8415(97)85010-4
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发表时间：
1997-04-01
影响因子：
10.9
通讯作者：
Wahl, R L
中科院分区：
文献类型：
--
作者：
Meyer, C R;Boes, J L;Wahl, R L
本文应用并评估了一个自动互信息为基础的注册算法在广泛的多模态体数据集。该算法需要很少或不需要预处理，最小的用户输入，并容易实现仿射，即线性或薄板样条（TPS）扭曲注册。我们已经在体模研究中评估了该算法，以及在选择的情况下，很少有其他算法可以执行，如果有的话，以证明这种新方法的价值。通过迭代改变配准参数以最大化互信息，对多模态灰度体数据集进行配准。在使用PET/CT的胸部体模的配准中以及在国家医学图书馆的Visible Male中使用MRI T2/T1加权采集来评估定量配准误差。证明了不同临床数据集的配准，包括PET/MRI脑部扫描的旋转-平移映射（具有显著缺失数据）、胸部PET/CT的全仿射映射和腹部SPECT/CT的旋转-平移映射。一个五点薄板样条（TPS）扭曲注册胸部PET/CT也证明。对于仿射临床配准，配准算法在3.5至31分钟的时间范围内收敛，对于TPS变形，配准算法在57分钟的时间范围内收敛。旋转-平移配准的平均误差向量长度在体模中测量为亚体素。更重要的是，旋转-平移算法即使在丢失数据的情况下也能很好地执行。所有节段的临床融合均为优质融合。我们的结论是，这种自动的，快速的，强大的算法显着增加的可能性，多模态注册将常规用于辅助临床诊断和治疗后评估在不久的将来。
This paper applies and evaluates an automatic mutual information-based registration algorithm across a broad spectrum of multimodal volume data sets. The algorithm requires little or no pre-processing, minimal user input and easily implements either affine, i.e. linear or thin-plate spline (TPS) warped registrations. We have evaluated the algorithm in phantom studies as well as in selected cases where few other algorithms could perform as well, if at all, to demonstrate the value of this new method. Pairs of multimodal gray-scale volume data sets were registered by iteratively changing registration parameters to maximize mutual information. Quantitative registration errors were assessed in registrations of a thorax phantom using PET/CT and in the National Library of Medicine's Visible Male using MRI T2-/T1-weighted acquisitions. Registrations of diverse clinical data sets were demonstrated including rotate-translate mapping of PET/MRI brain scans with significant missing data, full affine mapping of thoracic PET/CT and rotate-translate mapping of abdominal SPECT/CT. A five-point thin-plate spline (TPS) warped registration of thoracic PET/CT is also demonstrated. The registration algorithm converged in times ranging between 3.5 and 31 min for affine clinical registrations and 57 min for TPS warping. Mean error vector lengths for rotate-translate registrations were measured to be subvoxel in phantoms. More importantly the rotate-translate algorithm performs well even with missing data. The demonstrated clinical fusions are qualitatively excellent at all levels. We conclude that such automatic, rapid, robust algorithms significantly increase the likelihood that multimodality registrations will be routinely used to aid clinical diagnoses and post-therapeutic assessment in the near future.