首页> 外文会议>International Workshop on Medical Imaging and Augmented Reality(MIAR 2004); 20040819-20040820; Beijing; CN >Multimodal Brain Image Registration Based on Wavelet Transform Using SAD and MI
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Multimodal Brain Image Registration Based on Wavelet Transform Using SAD and MI

机译:基于SAD和MI的小波变换的多峰脑图像配准

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The multiresolution approach is commonly used to speed up the mutual-information (MI) based registration process. Conventionally, a Gaussian pyramid is often used as a multiresolution representation. However, in multi-modal medical image registration, MI-based methods with Gaussian pyramid may suffer from the problem of short capture ranges especially at the lower resolution levels. This paper proposes a novel and straightforward multimodal image registration method based on wavelet representation, in which two matching criteria are used including sum of difference (SAD) for improving the registration robustness and MI for assuring the registration accuracy. Experimental results show that the proposed method obtains a longer capture range than the traditional MI-based Gaussian pyramid method meanwhile maintaining comparable accuracy.
机译:多分辨率方法通常用于加速基于互信息(MI)的注册过程。按照惯例,高斯金字塔通常用作多分辨率表示。但是,在多模式医学图像配准中,具有高斯金字塔的基于MI的方法可能会遇到捕获范围短的问题,尤其是在较低分辨率级别上。本文提出了一种基于小波表示的新颖,直接的多模态图像配准方法,该方法采用两种匹配标准,包括差分和(SAD)和配准度(MI),以提高配准的鲁棒性和配准精度。实验结果表明,与传统的基于MI的高斯金字塔方法相比,所提方法具有更长的捕获范围,同时保持了相当的精度。

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