Suppr超能文献

扩散 MRI 中的指纹方位分布函数可检测到更小的交叉角。

Fingerprinting Orientation Distribution Functions in diffusion MRI detects smaller crossing angles.

机构信息

Center for Advanced Imaging Innovation and Research (CAI(2)R), NYU School of Medicine, New York, NY, USA; Center for Biomedical Imaging, Dept. of Radiology, NYU School of Medicine, New York, NY, USA.

Center for Advanced Imaging Innovation and Research (CAI(2)R), NYU School of Medicine, New York, NY, USA; Center for Biomedical Imaging, Dept. of Radiology, NYU School of Medicine, New York, NY, USA; The Sackler Institute of Graduate Biomedical Sciences, NYU School of Medicine, New York, NY, USA.

出版信息

Neuroimage. 2019 Sep;198:231-241. doi: 10.1016/j.neuroimage.2019.05.024. Epub 2019 May 16.

Abstract

Diffusion tractography is routinely used to study white matter architecture and brain connectivity in vivo. A key step for successful tractography of neuronal tracts is the correct identification of tract directions in each voxel. Here we propose a fingerprinting-based methodology to identify these fiber directions in Orientation Distribution Functions, dubbed ODF-Fingerprinting (ODF-FP). In ODF-FP, fiber configurations are selected based on the similarity between measured ODFs and elements in a pre-computed library. In noisy ODFs, the library matching algorithm penalizes the more complex fiber configurations. ODF simulations and analysis of bootstrapped partial and whole-brain in vivo datasets show that the ODF-FP approach improves the detection of fiber pairs with small crossing angles while maintaining fiber direction precision, which leads to better tractography results. Rather than focusing on the ODF maxima, the ODF-FP approach uses the whole ODF shape to infer fiber directions to improve the detection of fiber bundles with small crossing angle. The resulting fiber directions aid tractography algorithms in accurately displaying neuronal tracts and calculating brain connectivity.

摘要

弥散张量成像技术常用于活体研究白质结构和大脑连接。成功追踪神经元束的关键步骤是正确识别每个体素中的束方向。在这里,我们提出了一种基于指纹的方法来识别取向分布函数中的这些纤维方向,称为 ODF 指纹(ODF-FP)。在 ODF-FP 中,根据测量的 ODF 与预计算库中元素之间的相似性选择纤维构型。在噪声 ODF 中,库匹配算法会惩罚更复杂的纤维构型。ODF 模拟和对 bootstrap 部分和全脑活体数据集的分析表明,ODF-FP 方法提高了对具有小交叉角的纤维对的检测能力,同时保持纤维方向精度,从而获得更好的追踪结果。ODF-FP 方法不是专注于 ODF 最大值,而是使用整个 ODF 形状来推断纤维方向,以提高对具有小交叉角的纤维束的检测能力。得到的纤维方向有助于追踪算法准确显示神经元束并计算大脑连接。

相似文献

7
9
Tractometer: towards validation of tractography pipelines.束径仪:用于追踪技术管道的验证。
Med Image Anal. 2013 Oct;17(7):844-57. doi: 10.1016/j.media.2013.03.009. Epub 2013 Apr 25.

引用本文的文献

4
Sparse Blind Spherical Deconvolution of diffusion weighted MRI.扩散加权磁共振成像的稀疏盲球形反卷积
Front Neurosci. 2024 May 22;18:1385975. doi: 10.3389/fnins.2024.1385975. eCollection 2024.

本文引用的文献

5
Structural Brain Connectome and Cognitive Impairment in Parkinson Disease.帕金森病的结构脑连接组与认知障碍。
Radiology. 2017 May;283(2):515-525. doi: 10.1148/radiol.2016160274. Epub 2016 Dec 7.
8
Denoising of diffusion MRI using random matrix theory.使用随机矩阵理论对扩散磁共振成像进行去噪
Neuroimage. 2016 Nov 15;142:394-406. doi: 10.1016/j.neuroimage.2016.08.016. Epub 2016 Aug 11.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验