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

机译:活动图集:将3D解剖模型与纹理探测器相结合

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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:虽然诸如FMRI等现代成像技术已经开辟了在体内研究大脑的激动人心的可能性,但组织学部分仍然是在神经元水平上学习脑解剖学的最佳方法。建立组织学阿特拉斯的程序改变了1909年以来的几乎没有变化,并且识别脑区是仅由经验丰富的神经反应主义者进行的劳动密集型过程。现有的数字地图集,例如Allen参考标签,使用下采样的图像构建,并且不能可靠地映射诸如脑干的低对比度部件,这通常基于高分辨率蜂窝纹理注释。我们开发了一种数字地图集方法,这些方法结合了关于3D组织的信息和不同结构的详细纹理。使用该方法我们开发了一个鼠标脑干的图表,目前没有良好的地图集的区域。我们的地图集是“活跃”的,因为它可以用于自动对齐组织学堆叠到地图集,从而减少神经制死者的工作。

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