Lu Huanxiang, Cattin Philippe C, Reyes Mauricio
Institute for Surgical Technology & Biomechanics, University of Bern, CH-3014, Switzerland.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:5951-4. doi: 10.1109/IEMBS.2010.5627562.
In this paper we present a novel hybrid approach for multimodal medical image registration based on diffeomorphic demons. Diffeomorphic demons have proven to be a robust and efficient way for intensity-based image registration. A very recent extension even allows to use mutual information (MI) as a similarity measure to registration multimodal images. However, due to the intensity correspondence uncertainty existing in some anatomical parts, it is difficult for a purely intensity-based algorithm to solve the registration problem. Therefore, we propose to combine the resulting transformations from both intensity-based and landmark-based methods for multimodal non-rigid registration based on diffeomorphic demons. Several experiments on different types of MR images were conducted, for which we show that a better anatomical correspondence between the images can be obtained using the hybrid approach than using either intensity information or landmarks alone.
在本文中，我们提出了一种基于微分同胚恶魔的新型多模态医学图像配准混合方法。微分同胚恶魔已被证明是基于强度的图像配准的一种强大而有效的方法。最近的一项扩展甚至允许使用互信息（MI）作为配准多模态图像的相似性度量。然而，由于某些解剖部位存在强度对应不确定性，纯粹基于强度的算法难以解决配准问题。因此，我们建议将基于强度和基于地标的方法所产生的变换相结合，用于基于微分同胚恶魔的多模态非刚性配准。我们对不同类型的磁共振图像进行了多项实验，结果表明，与单独使用强度信息或地标相比，使用混合方法可以在图像之间获得更好的解剖对应。
