Beijing Jiaotong Unversity, Beijing, China.
Med Biol Eng Comput. 2018 Nov;56(11):2151-2161. doi: 10.1007/s11517-018-1808-1. Epub 2018 Jun 4.
An atlas-based multimodal registration method for 2-dimension images with discrepancy structures was proposed in this paper. Atlas was utilized for complementing the discrepancy structure information in multimodal medical images. The scheme includes three steps: floating image to atlas registration, atlas to reference image registration, and field-based deformation. To evaluate the performance, a frame model, a brain model, and clinical images were employed in registration experiments. We measured the registration performance by the squared sum of intensity differences. Results indicate that this method is robust and performs better than the direct registration for multimodal images with discrepancy structures. We conclude that the proposed method is suitable for multimodal images with discrepancy structures. Graphical Abstract An Atlas-based multimodal registration method schematic diagram.
本文提出了一种基于图谱的具有差异结构的二维图像多模态配准方法。图谱用于补充多模态医学图像中的差异结构信息。该方案包括三个步骤：浮动图像到图谱的配准、图谱到参考图像的配准和基于场的变形。为了评估性能，在配准实验中使用了帧模型、脑模型和临床图像。我们通过强度差异的平方和来测量配准性能。结果表明，该方法对于具有差异结构的多模态图像是稳健的，并且比直接配准性能更好。我们得出结论，该方法适用于具有差异结构的多模态图像。
