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The Active Atlas: Combining 3D Anatomical Models with Texture Detectors

机译:主动地图集:将3D解剖模型与纹理检测器相结合

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While modern imaging technologies such as fMRI have opened exciting possibilities for studying the brain in vivo, histological sections remain the best way to study brain anatomy at the level of neurons. The procedure for building histological atlas changed little since 1909 and identifying brain regions is a still a labor intensive process performed only by experienced neuroanatomists. Existing digital atlases such as the Allen Reference Atlas are constructed using downsampled images and can not reliably map low-contrast parts such as brainstem, which is usually annotated based on high-resolution cellular texture. We have developed a digital atlas methodology that combines information about the 3D organization and the detailed texture of different structures. Using the methodology we developed an atlas for the mouse brainstem, a region for which there are currently no good atlases. Our atlas is "active" in that it can be used to automatically align a histological stack to the atlas, thus reducing the work of the neuroanatomist.
机译:尽管诸如fMRI的现代成像技术为体内研究大脑开辟了令人兴奋的可能性,但组织学切片仍是研究神经元水平的大脑解剖结构的最佳方法。自1909年以来,建立组织学地图集的过程几乎没有改变,并且仅由经验丰富的神经解剖学家执行才能确定大脑区域仍然是一项劳动密集型过程。现有的数字地图集(例如Allen参考地图集)是使用下采样图像构建的,无法可靠地映射低对比度的部分(例如脑干),而后者通常是基于高分辨率细胞纹理进行注释的。我们已经开发了一种数字地图集方法,该方法结合了有关3D组织和不同结构的详细纹理的信息。使用该方法,我们为小鼠脑干开发了地图集,该区域目前尚无良好的地图集。我们的地图集是“活跃的”,因为它可用于自动将组织学堆栈与地图集对齐,从而减少了神经解剖学家的工作。

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