Suppr超能文献

基于图谱的高密度漫射光学层析成像对人类视觉皮层成像的定量评估。

Quantitative evaluation of atlas-based high-density diffuse optical tomography for imaging of the human visual cortex.

作者信息

Wu Xue, Eggebrecht Adam T, Ferradal Silvina L, Culver Joseph P, Dehghani Hamid

机构信息

School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK.

Department of Radiology, Washington University School of Medicine, 4525 Scott Avenue, St Louis, MO, 63110, USA.

出版信息

Biomed Opt Express. 2014 Oct 13;5(11):3882-900. doi: 10.1364/BOE.5.003882. eCollection 2014 Nov 1.

Abstract

Image recovery in diffuse optical tomography (DOT) of the human brain often relies on accurate models of light propagation within the head. In the absence of subject specific models for image reconstruction, the use of atlas based models are showing strong promise. Although there exists some understanding in the use of some limited rigid model registrations in DOT, there has been a lack of a detailed analysis between errors in geometrical accuracy, light propagation in tissue and subsequent errors in dynamic imaging of recovered focal activations in the brain. In this work 11 different rigid registration algorithms, across 24 simulated subjects, are evaluated for DOT studies in the visual cortex. Although there exists a strong correlation (R(2) = 0.97) between geometrical surface error and internal light propagation errors, the overall variation is minimal when analysing recovered focal activations in the visual cortex. While a subject specific mesh gives the best results with a 1.2 mm average location error, no single algorithm provides errors greater than 4.5 mm. This work demonstrates that the use of rigid algorithms for atlas based imaging is a promising route when subject specific models are not available.

摘要

人脑扩散光学层析成像(DOT)中的图像重建通常依赖于头部内光传播的精确模型。在缺乏用于图像重建的个体特异性模型的情况下,基于图谱的模型显示出巨大潜力。尽管在DOT中对一些有限的刚性模型配准的使用已有一定了解,但在几何精度误差、组织中的光传播以及随后大脑中恢复的焦点激活动态成像中的误差之间,仍缺乏详细分析。在这项工作中,针对视觉皮层的DOT研究,对24个模拟对象的11种不同刚性配准算法进行了评估。尽管几何表面误差与内部光传播误差之间存在很强的相关性(R² = 0.97),但在分析视觉皮层中恢复的焦点激活时,总体变化很小。虽然个体特异性网格给出了最佳结果,平均位置误差为1.2毫米,但没有一种算法的误差大于4.5毫米。这项工作表明,在没有个体特异性模型时,使用基于图谱成像的刚性算法是一条很有前景的途径。

相似文献

1
Quantitative evaluation of atlas-based high-density diffuse optical tomography for imaging of the human visual cortex.
Biomed Opt Express. 2014 Oct 13;5(11):3882-900. doi: 10.1364/BOE.5.003882. eCollection 2014 Nov 1.
2
Atlas-based head modeling and spatial normalization for high-density diffuse optical tomography: in vivo validation against fMRI.
Neuroimage. 2014 Jan 15;85 Pt 1(0 1):117-26. doi: 10.1016/j.neuroimage.2013.03.069. Epub 2013 Apr 8.
3
Evaluation of rigid registration methods for whole head imaging in diffuse optical tomography.
Neurophotonics. 2015 Jul;2(3):035002. doi: 10.1117/1.NPh.2.3.035002. Epub 2015 Jul 21.
4
Validating atlas-guided DOT: a comparison of diffuse optical tomography informed by atlas and subject-specific anatomies.
Neuroimage. 2012 Sep;62(3):1999-2006. doi: 10.1016/j.neuroimage.2012.05.031. Epub 2012 May 23.
5
Back-propagation neural network-based reconstruction algorithm for diffuse optical tomography.
J Biomed Opt. 2018 Dec;24(5):1-12. doi: 10.1117/1.JBO.24.5.051407.
6
Fast noninvasive functional diffuse optical tomography for brain imaging.
J Biophotonics. 2018 Mar;11(3). doi: 10.1002/jbio.201600267. Epub 2017 Sep 25.
7
Impact of errors in experimental parameters on reconstructed breast images using diffuse optical tomography.
Biomed Opt Express. 2018 Feb 13;9(3):1130-1150. doi: 10.1364/BOE.9.001130. eCollection 2018 Mar 1.
8
Image quality analysis of high-density diffuse optical tomography incorporating a subject-specific head model.
Front Neuroenergetics. 2012 May 24;4:6. doi: 10.3389/fnene.2012.00006. eCollection 2012.
9
Subject-specific information enhances spatial accuracy of high-density diffuse optical tomography.
Front Neuroergon. 2024 Feb 19;5:1283290. doi: 10.3389/fnrgo.2024.1283290. eCollection 2024.

引用本文的文献

1
Robust photogrammetric scalp morphology estimation for functional optical neuroimaging.
Neurophotonics. 2025 Jul;12(3):035002. doi: 10.1117/1.NPh.12.3.035002. Epub 2025 Jul 28.
2
Effects of atlas-based anatomy on modelled light transport in the neonatal head.
Phys Med Biol. 2023 Jul 3;68(13):135019. doi: 10.1088/1361-6560/acd48c.
3
Optical imaging and spectroscopy for the study of the human brain: status report.
Neurophotonics. 2022 Aug;9(Suppl 2):S24001. doi: 10.1117/1.NPh.9.S2.S24001. Epub 2022 Aug 30.
4
Variability in atlas registration of optical intrinsic signal imaging and its effect on functional connectivity analysis.
J Opt Soc Am A Opt Image Sci Vis. 2021 Feb 1;38(2):245-252. doi: 10.1364/JOSAA.410447.
5
Global motion detection and censoring in high-density diffuse optical tomography.
Hum Brain Mapp. 2020 Oct 1;41(14):4093-4112. doi: 10.1002/hbm.25111. Epub 2020 Jul 10.
6
Brain segmentation, spatial censoring, and averaging techniques for optical functional connectivity imaging in mice.
Biomed Opt Express. 2019 Oct 29;10(11):5952-5973. doi: 10.1364/BOE.10.005952. eCollection 2019 Nov 1.
7
Graph- and finite element-based total variation models for the inverse problem in diffuse optical tomography.
Biomed Opt Express. 2019 May 2;10(6):2684-2707. doi: 10.1364/BOE.10.002684. eCollection 2019 Jun 1.
8
High-density diffuse optical tomography for imaging human brain function.
Rev Sci Instrum. 2019 May;90(5):051101. doi: 10.1063/1.5086809.
9
Lightweight sCMOS-based high-density diffuse optical tomography.
Neurophotonics. 2018 Jul;5(3):035006. doi: 10.1117/1.NPh.5.3.035006. Epub 2018 Aug 17.
10
L-norm based nonlinear reconstruction improves quantitative accuracy of spectral diffuse optical tomography.
Biomed Opt Express. 2018 Mar 2;9(4):1423-1444. doi: 10.1364/BOE.9.001423. eCollection 2018 Apr 1.

本文引用的文献

1
Mapping distributed brain function and networks with diffuse optical tomography.
Nat Photonics. 2014 Jun;8(6):448-454. doi: 10.1038/nphoton.2014.107.
2
Algorithm to find high density EEG scalp coordinates and analysis of their correspondence to structural and functional regions of the brain.
J Neurosci Methods. 2014 May 30;229:84-96. doi: 10.1016/j.jneumeth.2014.04.020. Epub 2014 Apr 24.
3
Optical bedside monitoring of cerebral blood flow in acute ischemic stroke patients during head-of-bed manipulation.
Stroke. 2014 May;45(5):1269-74. doi: 10.1161/STROKEAHA.113.004116. Epub 2014 Mar 20.
5
Atlas-based head modeling and spatial normalization for high-density diffuse optical tomography: in vivo validation against fMRI.
Neuroimage. 2014 Jan 15;85 Pt 1(0 1):117-26. doi: 10.1016/j.neuroimage.2013.03.069. Epub 2013 Apr 8.
6
High-density diffuse optical tomography of term infant visual cortex in the nursery.
J Biomed Opt. 2012 Aug;17(8):081414. doi: 10.1117/1.JBO.17.8.081414.
7
Image quality analysis of high-density diffuse optical tomography incorporating a subject-specific head model.
Front Neuroenergetics. 2012 May 24;4:6. doi: 10.3389/fnene.2012.00006. eCollection 2012.
8
Validating atlas-guided DOT: a comparison of diffuse optical tomography informed by atlas and subject-specific anatomies.
Neuroimage. 2012 Sep;62(3):1999-2006. doi: 10.1016/j.neuroimage.2012.05.031. Epub 2012 May 23.
9
A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping.
Neuroimage. 2012 Jul 16;61(4):1120-8. doi: 10.1016/j.neuroimage.2012.01.124. Epub 2012 Feb 10.
10
Somatosensory activation of two fingers can be discriminated with ultrahigh-density diffuse optical tomography.
Neuroimage. 2012 Feb 15;59(4):3201-11. doi: 10.1016/j.neuroimage.2011.11.062. Epub 2011 Dec 1.

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