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多模态全身 MRI 拼图的注册策略。

Registration strategies for multi-modal whole-body MRI mosaicing.

机构信息

Vrije Universiteit Brussel (VUB), Department of Electronics and Informatics (ETRO), Brussels, Belgium.

imec, Leuven, Belgium.

出版信息

Magn Reson Med. 2018 Mar;79(3):1684-1695. doi: 10.1002/mrm.26787. Epub 2017 Jun 21.

Abstract

PURPOSE

To test and compare different registration approaches for performing whole-body diffusion-weighted (wbDWI) image station mosaicing, and its alignment to corresponding anatomical T whole-body image.

METHODS

Four different registration strategies aiming at mosaicing of diffusion-weighted image stations, and their alignment to the corresponding whole-body anatomical image, were proposed and evaluated. These included two-step approaches, where diffusion-weighted stations are first combined in a pairwise (Strategy 1) or groupwise (Strategy 2) manner and later non-rigidly aligned to the anatomical image; a direct pairwise mapping of DWI stations onto the anatomical image (Strategy 3); and simultaneous mosaicing of DWI and alignment to the anatomical image (Strategy 4). Additionally, different images driving the registration were investigated. Experiments were performed for 20 whole-body images of patients with bone metastases.

RESULTS

Strategies 1 and 2 showed significant improvement in mosaicing accuracy with respect to the non-registered images (P < 0.006). Strategy 2 based on ADC images increased the alignment accuracy between DWI stations and the T whole-body image (P = 0.0009).

CONCLUSIONS

A two-step registration strategy, relying on groupwise mosaicing of the ADC stations and subsequent registration to T , provided the best compromise between whole-body DWI image quality and multi-modal alignment. Magn Reson Med 79:1684-1695, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

摘要

目的

测试和比较用于进行全身弥散加权(wbDWI)图像拼接的不同配准方法,并将其与相应的解剖 T 全身图像对齐。

方法

提出并评估了四种不同的配准策略,旨在对扩散加权图像站进行拼接,并将其与相应的全身解剖图像对齐。这些策略包括两步法,即先将扩散加权站以两两(策略 1)或分组(策略 2)的方式组合,然后将其与解剖图像进行非刚性对齐;将 DWI 站直接映射到解剖图像(策略 3);以及同时对 DWI 进行拼接并与解剖图像对齐(策略 4)。此外,还研究了不同的图像来驱动配准。对 20 例患有骨转移的患者的全身图像进行了实验。

结果

策略 1 和 2 在拼接精度方面相对于未注册的图像有显著提高(P < 0.006)。基于 ADC 图像的策略 2 提高了 DWI 站与 T 全身图像之间的对齐精度(P = 0.0009)。

结论

基于 ADC 站的分组拼接和随后与 T 图像的注册的两步注册策略,在全身 DWI 图像质量和多模态对齐之间提供了最佳的折衷。磁共振医学 79:1684-1695, 2018. © 2017 国际磁共振学会。

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