Multimodal Image Registration Through Simultaneous Segmentation

Iman Aganj

doi:10.1109/LSP.2017.2754263

2017-11-01

Iman Aganj *

Bruce Fischl

DOI：10.1109/LSP.2017.2754263

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摘要

En 中文

多模态图像配准促进来自用不同模态采集的图像的互补信息的组合。大多数现有方法需要计算图像的联合直方图，而一些方法在交替迭代中执行联合分割和配准。在这封信中，我们介绍了一种新的非信息理论方法，用于成对多模态图像配准，其中使用两幅图像的分割误差被视为配准成本函数。我们通过对多对比脑图像进行刚性配准来对我们的方法进行经验评估，并证明与几种现有方法相比，所提出的技术产生的结果通常具有更高的配准精度。

Keyword:

Multimodal image registration

segmentation-based (SB) image registration

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对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

IEEE Signal Processing Magazine

IF:

9.6

论文数:

1.1W

被引数:

1.7W

机构

Harvard University

学者数:

26.5W

论文数: 22.0W

被引数: 28.7W

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