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基于图谱的小鼠脑部分割评估。

Evaluation of Atlas based Mouse Brain Segmentation.

作者信息

Lee Joohwi, Jomier Julien, Aylward Stephen, Tyszka Mike, Moy Sheryl, Lauder Jean, Styner Martin

机构信息

Department of Computer Science, University of North Carolina, Chapel Hill NC, USA.

出版信息

Proc SPIE Int Soc Opt Eng. 2009 Feb 1;7259:725943-725949. doi: 10.1117/12.812762.

Abstract

Magentic Reasonance Imaging for mouse phenotype study is one of the important tools to understand human diseases. In this paper, we present a fully automatic pipeline for the process of morphometric mouse brain analysis. The method is based on atlas-based tissue and regional segmentation, which was originally developed for the human brain. To evaluate our method, we conduct a qualitative and quantitative validation study as well as compare of b-spline and fluid registration methods as components in the pipeline. The validation study includes visual inspection, shape and volumetric measurements and stability of the registration methods against various parameter settings in the processing pipeline. The result shows both fluid and b-spline registration methods work well in murine settings, but the fluid registration is more stable. Additionally, we evaluated our segmentation methods by comparing volume differences between Fmr1 FXS in FVB background vs C57BL/6J mouse strains.

摘要

用于小鼠表型研究的磁共振成像(MRI)是理解人类疾病的重要工具之一。在本文中,我们提出了一种用于小鼠脑形态计量分析过程的全自动流程。该方法基于基于图谱的组织和区域分割,最初是为人类大脑开发的。为了评估我们的方法,我们进行了定性和定量验证研究,并比较了作为流程组件的B样条和流体配准方法。验证研究包括视觉检查、形状和体积测量以及配准方法在处理流程中针对各种参数设置的稳定性。结果表明,流体和B样条配准方法在小鼠模型中都能很好地工作,但流体配准更稳定。此外,我们通过比较FVB背景下的Fmr1脆性X综合征(FXS)与C57BL/6J小鼠品系之间的体积差异来评估我们的分割方法。

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