首页> 外文会议>Image Processing pt.2; Progress in Biomedical Optics and Imaging; vol.7 no.30 >Validation of elastic registration algorithms based on adaptive irregular grids for medical applications
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Validation of elastic registration algorithms based on adaptive irregular grids for medical applications

机译:基于自适应不规则网格的弹性配准算法在医学应用中的验证

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Elastic registration of medical images, i.e. finding a non-affine transformation such that corresponding image structures correctly align, is an active field of current research. Registration algorithms have to be validated in order to show that they fulfill the requirements of a particular clinical application. Furthermore, validation strategies compare the performance of different registration algorithms and can hence judge which algorithm is best suited to meet the requirements of a target application. In the literature, validation strategies for rigid registration algorithms have been analyzed. For a known ground truth they assess the displacement error at-a few isolated landmarks. This approach is not sufficient for elastic transformations described by a huge number of parameters and the non-linear inter-landmark behaviour. Hence we consider the displacement error averaged over all pixels in the whole image or in a region-of-interest of clinical relevance. Using artificially, but realistically deformed images of the application domain, we use this quality measure to analyze an elastic registration based on transformations defined on adaptive irregular grids for the following clinical applications: Magnetic Resonance (MR) images of freely moving joints for orthopedic investigations, thoracic Computed Tomography (CT) images for the detection of pulmonary embolisms, and transmission images as used for the attenuation correction and registration of independently acquired Positron Emission Tomography (PET) and CT images. The definition of a region-of-interest allows to restrict the analysis of the registration accuracy to clinically relevant image areas. The behaviour of the displacement error as a function of the number of transformation control points and their placement can be used for identifying the best strategy for the initial placement of the control points allowing the same registration accuracy to be achieved with significantly less control points than using a regular control point arrangement.
机译:医学图像的弹性配准,即发现非仿射变换,以使相应的图像结构正确对准,是当前研究的活跃领域。注册算法必须经过验证,以表明它们满足特定临床应用程序的要求。此外,验证策略会比较不同注册算法的性能,因此可以判断哪种算法最适合满足目标应用程序的要求。在文献中,已经分析了用于刚性配准算法的验证策略。对于已知的地面真相,他们评估了几个孤立地标处的位移误差。对于由大量参数和非线性地标间行为描述的弹性变换,这种方法是不够的。因此,我们考虑在整个图像中或在临床相关的感兴趣区域中,所有像素平均的位移误差。通过使用应用程序域的人工但实际变形的图像,我们使用此质量度量来分析基于适应性不规则网格定义的转换的弹性配准,用于以下临床应用:自由移动关节的磁共振(MR)图像,用于骨科检查,胸部计算机断层扫描(CT)图像用于检测肺栓塞,以及用于衰减校正和独立采集的正电子发射断层扫描(PET)和CT图像的透射图像。感兴趣区域的定义允许将配准精度的分析限于临床相关的图像区域。位移误差随变换控制点数量及其放置而变化的行为可用于识别控制点初始放置的最佳策略,从而与使用控制点相比,使用更少的控制点即可实现相同的配准精度常规控制点安排。

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