Registration of dynamic renal MR images using neurobiological model of saliency

D. Mahapatra, Ying Sun
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引用次数: 43

Abstract

In this paper we propose the use of a neurobiology-based saliency measure to improve the performance of a quantitative- qualitative measure of mutual information for rigid registration of 4D renal perfusion MR images. Our registration method assigns greater importance to more salient voxels by applying a soft thresholding function to normalized saliency values. The resulting saliency map is a better representation of what is truly visually salient than an entropy-based saliency map. Our tests on real patient datasets show that incorporating this saliency measure produces better registration results than traditional entropy-based approaches.
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应用显著性神经生物学模型的动态肾脏MR图像配准
在本文中,我们提出使用基于神经生物学的显著性措施来提高定量-定性互信息措施的性能,用于4D肾灌注MR图像的刚性配准。我们的配准方法通过对标准化的显著性值应用软阈值函数来赋予更显著的体素更大的重要性。由此产生的显著性图比基于熵的显著性图更好地表示了真正的视觉显著性。我们对真实患者数据集的测试表明,结合这种显著性度量比传统的基于熵的方法产生更好的注册结果。
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