Registration Strategies and Similarity Measures for Three-dimensional Ultrasound Mosaicing

Registration Strategies and Similarity Measures for Three-dimensional Ultrasound Mosaicing
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三维超声镶嵌的配准策略和相似度测量

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通讯作者:
Nassir Navab
Nassir Navab
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作者:
C. Wachinger;W. Wein;Nassir Navab

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Rationale and Objectives: The creation of 2D ultrasound mosaics is becoming a common clinical practice with a high clinical value. The next step coming along with the increasing availability of 2D array transducers is the creation of 3D mosaics. The correct alignment of multiple ultrasound images is, however, a complex task. In the literature of ultrasound registration, the alignment of two images was often addressed; however, not the alignment of multiple images. Therefore, we propose registration strategies for multiple image alignment and ultrasound specific similarity measures, which are able to cope with problems arising by aligning ultrasound images. Materials and Methods: In this article, we investigate the following strategies for multiple image alignment: pairwise registration with a successive Lie group normalization and simultaneous registration, which urges the usage of multivariate similarity measures. We propose alternative multivariate extensions for similarity measures based on a maximum likelihood framework. Moreover, we take the inherent contamination of ultrasound images by speckle patterns into consideration by using alternative noise models based on multi-plicative Rayleigh distributed noise. This leads us to ultrasound specific similarity measures. Results: We compare the performances of pairwise and simultaneous registration approaches for the mosaicing scenario. Bivariate similarity measures are highly overlap dependent , so that they rather favor the total overlap of the images than their correct alignment. Using ultrasound specific bivariate measures leads to better results, however, a local optimum at the total overlap remains. In contrast, the derived multivariate similarity measures have a clear and single optimum at the correct alignment of the volumes. Conclusion: The experiments indicate that standard, pairwise registration techniques have problems by aligning multiple ultrasound images with partial overlap. We demonstrate that the usage of an ultrasound specific similarity measure leads to better results for pairwise registration. The highest robustness, however, can be achieved by using simultaneous registration with the developed multivariate similarity measures.