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Demon registration for 3D images obtained by serial block face scanning electron microscopy

机译:通过串行块面扫描电子显微镜获得的3D图像的恶魔配准

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In the last decade “Demon”-based matching algorithms have largely demonstrated their efficiency in non-rigid registration of clinical and biomedical images. This paper present an experimental study of a symmetrized variant of Thirion's demons algorithm applied to the realignment of 3D images obtained by serial block face scanning electron microscopy (SBFSEM). Because demons are sensible to local intensity difference, it is necessary to ensure that both images have matching intensity distributions. We propose to perform the demon registration on an image intensity transformation associating total-variation denoising and modified contrast-limited adaptive histogram equalization. We compare the performance of the presented method with a B-spline based free form deformation method on a SBFSEM stack. This preliminary study shows that the demon registration applied to the proposed image intensity transformation is a fast and robust algorithm. Besides it always exhibit a better compromise in term registration accuracy and smoothness of the transformation field than the B-spline method.
机译:在过去的十年中,基于“ Demon”的匹配算法已在很大程度上证明了其在临床和生物医学图像的非刚性配准中的效率。本文介绍了Thirion恶魔算法的对称变体的实验研究,该算法适用于通过串行块面扫描电子显微镜(SBFSEM)获得的3D图像的重新对齐。因为恶魔对局部强度差很敏感,所以有必要确保两个图像都具有匹配的强度分布。我们建议在图像强度转换上执行恶魔配准,该图像强度转换将总变化量降噪与改进的对比度限制自适应直方图均衡化相关联。我们在SBFSEM堆栈上比较了所提出的方法与基于B样条的自由形式变形方法的性能。这项初步研究表明,将恶魔配准应用于所提出的图像强度变换是一种快速且鲁棒的算法。此外,与B样条方法相比,它始终在术语配准精度和变换字段的平滑度方面表现出更好的折衷。

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