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普通狒狒大脑:来自89只个体的MRI模板和组织概率图谱。

The average baboon brain: MRI templates and tissue probability maps from 89 individuals.

作者信息

Love Scott A, Marie Damien, Roth Muriel, Lacoste Romain, Nazarian Bruno, Bertello Alice, Coulon Olivier, Anton Jean-Luc, Meguerditchian Adrien

机构信息

Laboratoire de Psychologie Cognitive, UMR7290, Université Aix-Marseille/CNRS, 13331 Marseille, France; Station de Primatologie, CNRS, UPS846, 13790 Rousset, France; Institut des Neurosciences de la Timone, UMR7289, Université Aix-Marseille/CNRS, 13005 Marseille, France.

Laboratoire de Psychologie Cognitive, UMR7290, Université Aix-Marseille/CNRS, 13331 Marseille, France; Station de Primatologie, CNRS, UPS846, 13790 Rousset, France.

出版信息

Neuroimage. 2016 May 15;132:526-533. doi: 10.1016/j.neuroimage.2016.03.018. Epub 2016 Mar 11.

Abstract

The baboon (Papio) brain is a remarkable model for investigating the brain. The current work aimed at creating a population-average baboon (Papio anubis) brain template and its left/right hemisphere symmetric version from a large sample of T1-weighted magnetic resonance images collected from 89 individuals. Averaging the prior probability maps output during the segmentation of each individual also produced the first baboon brain tissue probability maps for gray matter, white matter and cerebrospinal fluid. The templates and the tissue probability maps were created using state-of-the-art, freely available software tools and are being made freely and publicly available: http://www.nitrc.org/projects/haiko89/ or http://lpc.univ-amu.fr/spip.php?article589. It is hoped that these images will aid neuroimaging research of the baboon by, for example, providing a modern, high quality normalization target and accompanying standardized coordinate system as well as probabilistic priors that can be used during tissue segmentation.

摘要

狒狒(Papio)大脑是研究大脑的一个出色模型。当前的工作旨在从89只个体的大量T1加权磁共振图像样本中创建一个群体平均狒狒(埃及狒狒)大脑模板及其左右半球对称版本。对每个个体分割过程中输出的先验概率图进行平均,还生成了第一张狒狒大脑灰质、白质和脑脊液的脑组织概率图。这些模板和组织概率图是使用最先进的免费软件工具创建的,并将免费公开提供:http://www.nitrc.org/projects/haiko89/http://lpc.univ-amu.fr/spip.php?article589 。希望这些图像能通过例如提供一个现代、高质量的归一化目标以及配套的标准化坐标系,以及在组织分割过程中可使用的概率先验,来辅助狒狒的神经成像研究。

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