Suppr超能文献

用于量化海马体和杏仁核体积的自动分割与手动追踪的比较。

A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes.

作者信息

Morey Rajendra A, Petty Christopher M, Xu Yuan, Hayes Jasmeet Pannu, Wagner H Ryan, Lewis Darrell V, LaBar Kevin S, Styner Martin, McCarthy Gregory

机构信息

Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, NC 27710, USA.

出版信息

Neuroimage. 2009 Apr 15;45(3):855-66. doi: 10.1016/j.neuroimage.2008.12.033. Epub 2008 Dec 30.

Abstract

Large databases of high-resolution structural MR images are being assembled to quantitatively examine the relationships between brain anatomy, disease progression, treatment regimens, and genetic influences upon brain structure. Quantifying brain structures in such large databases cannot be practically accomplished by expert neuroanatomists using hand-tracing. Rather, this research will depend upon automated methods that reliably and accurately segment and quantify dozens of brain regions. At present, there is little guidance available to help clinical research groups in choosing such tools. Thus, our goal was to compare the performance of two popular and fully automated tools, FSL/FIRST and FreeSurfer, to expert hand tracing in the measurement of the hippocampus and amygdala. Volumes derived from each automated measurement were compared to hand tracing for percent volume overlap, percent volume difference, across-sample correlation, and 3-D group-level shape analysis. In addition, sample size estimates for conducting between-group studies were computed for a range of effect sizes. Compared to hand tracing, hippocampal measurements with FreeSurfer exhibited greater volume overlap, smaller volume difference, and higher correlation than FIRST, and sample size estimates with FreeSurfer were closer to hand tracing. Amygdala measurement with FreeSurfer was also more highly correlated to hand tracing than FIRST, but exhibited a greater volume difference than FIRST. Both techniques had comparable volume overlap and similar sample size estimates. Compared to hand tracing, a 3-D shape analysis of the hippocampus showed FreeSurfer was more accurate than FIRST, particularly in the head and tail. However, FIRST more accurately represented the amygdala shape than FreeSurfer, which inflated its anterior and posterior surfaces.

摘要

高分辨率结构磁共振成像的大型数据库正在组建中,用于定量研究脑解剖结构、疾病进展、治疗方案以及基因对脑结构的影响之间的关系。在如此庞大的数据库中,由专业神经解剖学家通过手工追踪来定量脑结构实际上是无法完成的。相反,这项研究将依赖于能够可靠且准确地分割和量化数十个脑区的自动化方法。目前,几乎没有可用的指导来帮助临床研究团队选择此类工具。因此,我们的目标是比较两种常用的全自动工具FSL/FIRST和FreeSurfer在测量海马体和杏仁核方面与专家手工追踪的性能。将每种自动化测量得出的体积与手工追踪结果进行比较,以计算体积重叠百分比、体积差异百分比、样本间相关性以及三维组水平形状分析。此外,针对一系列效应大小计算了进行组间研究所需的样本量估计值。与手工追踪相比,FreeSurfer对海马体的测量在体积重叠方面更大,体积差异更小,相关性更高,且FreeSurfer的样本量估计值更接近手工追踪。FreeSurfer对杏仁核的测量与手工追踪的相关性也高于FIRST,但体积差异比FIRST更大。两种技术的体积重叠相当,样本量估计值相似。与手工追踪相比,对海马体的三维形状分析表明FreeSurfer比FIRST更准确,尤其是在头部和尾部。然而,FIRST比FreeSurfer更准确地呈现了杏仁核的形状,FreeSurfer夸大了其前后表面。

相似文献

1
A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes.
Neuroimage. 2009 Apr 15;45(3):855-66. doi: 10.1016/j.neuroimage.2008.12.033. Epub 2008 Dec 30.
3
Accuracy of automated amygdala MRI segmentation approaches in Huntington's disease in the IMAGE-HD cohort.
Hum Brain Mapp. 2020 May;41(7):1875-1888. doi: 10.1002/hbm.24918. Epub 2020 Feb 7.
4
Charting the human amygdala development across childhood and adolescence: Manual and automatic segmentation.
Dev Cogn Neurosci. 2021 Dec;52:101028. doi: 10.1016/j.dcn.2021.101028. Epub 2021 Oct 28.
8
Multi-atlas segmentation of the whole hippocampus and subfields using multiple automatically generated templates.
Neuroimage. 2014 Nov 1;101:494-512. doi: 10.1016/j.neuroimage.2014.04.054. Epub 2014 Apr 29.
9
Amygdalar and hippocampal volume: A comparison between manual segmentation, Freesurfer and VBM.
J Neurosci Methods. 2015 Sep 30;253:254-61. doi: 10.1016/j.jneumeth.2015.05.024. Epub 2015 Jun 6.

引用本文的文献

1
Baby Open Brains: An open-source dataset of infant brain segmentations.
Sci Data. 2025 Aug 14;12(1):1423. doi: 10.1038/s41597-025-05404-y.
2
A comprehensive and reliable protocol for manual segmentation of the human claustrum using high-resolution MRI.
Brain Struct Funct. 2025 Aug 13;230(7):134. doi: 10.1007/s00429-025-02993-7.
3
Automated segmentation for cortical thickness of the medial perirhinal cortex.
Sci Rep. 2025 Apr 28;15(1):14903. doi: 10.1038/s41598-025-98399-w.
6
Hippocampal volume asymmetry in Alzheimer disease: A systematic review and meta-analysis.
Medicine (Baltimore). 2025 Mar 7;104(10):e41662. doi: 10.1097/MD.0000000000041662.
7
A Case for Automated Segmentation of MRI Data in Milder Neurodegenerative Diseases.
medRxiv. 2025 Feb 20:2025.02.18.25322304. doi: 10.1101/2025.02.18.25322304.
10
Exploring the Impact of Variability in Cell Segmentation and Tracking Approaches.
Microsc Res Tech. 2025 Mar;88(3):716-731. doi: 10.1002/jemt.24715. Epub 2024 Nov 16.

本文引用的文献

2
Hippocampal volume and 2-year outcome in depression.
Br J Psychiatry. 2008 Jun;192(6):472-3. doi: 10.1192/bjp.bp.107.040378.
3
FreeSurfer-initiated fully-automated subcortical brain segmentation in MRI using Large Deformation Diffeomorphic Metric Mapping.
Neuroimage. 2008 Jul 1;41(3):735-46. doi: 10.1016/j.neuroimage.2008.03.024. Epub 2008 Mar 26.
5
Subcortical and cerebellar atrophy in mesial temporal lobe epilepsy revealed by automatic segmentation.
Epilepsy Res. 2008 May;79(2-3):130-8. doi: 10.1016/j.eplepsyres.2008.01.006. Epub 2008 Mar 21.
7
A comparison of methods for the automated calculation of volumes and atrophy rates in the hippocampus.
Neuroimage. 2008 May 1;40(4):1655-71. doi: 10.1016/j.neuroimage.2008.01.012. Epub 2008 Jan 26.
8
Registration and machine learning-based automated segmentation of subcortical and cerebellar brain structures.
Neuroimage. 2008 Jan 1;39(1):238-47. doi: 10.1016/j.neuroimage.2007.05.063. Epub 2007 Aug 22.
10
3D comparison of hippocampal atrophy in amnestic mild cognitive impairment and Alzheimer's disease.
Brain. 2006 Nov;129(Pt 11):2867-73. doi: 10.1093/brain/awl274. Epub 2006 Oct 3.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验