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首页> 外文会议>Conference on Medical Imaging 2008: Imaging Processing; 20080217-19; San Diego,CA(US) >Ultrasound Specific Similarity Measures for Three-Dimensional Mosaicing
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Ultrasound Specific Similarity Measures for Three-Dimensional Mosaicing

机译：三维镶嵌的超声特定相似性度量

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The introduction of 2D array ultrasound transducers enables the instantaneous acquisition of ultrasound volumes in the clinical practice. The next step coming along is the combination of several scans to create compounded volumes that provide an extended field-of-view, so called mosaics. The correct alignment of multiple images, which is a complex task, forms the basis of mosaicing. Especially the simultaneous intensity-based registration has many properties making it a good choice for ultrasound mosaicing in comparison to the pairwise one. Fundamental for each registration approach is a suitable similarity measure. So far, only standard measures like SSD, NNC, CR, and MI were used for mosaicing, which implicitly assume an additive Gaussian distributed noise. For ultrasound images, which are degraded by speckle patterns, alternative noise models based on multiplicative Rayleigh distributed noise were proposed in the field of motion estimation. Setting these models into the maximum likelihood estimation framework, which enables the mathematical modeling of the registration process, led us to ultrasound specific bivariate similarity measures. Subsequently, we used an extension of the maximum likelihood estimation framework, which we developed in a previous work, to also derive multivariate measures. They allow us to perform ultrasound specific simultaneous registration for mosaicing. These measures have a higher potential than afore mentioned standard measures since they are specifically designed to cope with problems arising from the inherent contamination of ultrasound images by speckle patterns. The results of the experiments that we conducted on a typical mosaicing scenario with only partly overlapping images confirm this assumption.
机译：二维阵列超声换能器的引入使得在临床实践中可以瞬时采集超声体积。接下来的步骤是几次扫描的组合，以创建可提供扩展视场（称为镶嵌）的复合体积。多个图像的正确对齐是一项复杂的任务，它构成了镶嵌的基础。特别是基于强度的同时配准具有许多特性，与成对的相比，它是超声镶嵌的不错选择。每种注册方法的基础都是合适的相似性度量。到目前为止，只有标准度量（例如SSD，NNC，CR和MI）用于镶嵌，这些镶嵌隐含地假定了加性高斯分布噪声。对于由于斑点图案而退化的超声图像，在运动估计领域中提出了基于乘性瑞利分布噪声的替代噪声模型。将这些模型设置为最大似然估计框架后，就可以对配准过程进行数学建模，从而使我们获得了超声特定的双变量相似性度量。随后，我们使用了在先前工作中开发的最大似然估计框架的扩展，也得出了多变量测度。它们使我们能够执行超声特定的同时配准进行镶嵌。这些措施比以前提到的标准措施具有更高的潜力，因为它们专门设计用于解决由于斑点图案而对超声图像的固有污染所引起的问题。我们在仅具有部分重叠图像的典型镶嵌场景下进行的实验结果证实了这一假设。

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