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首页> 外文期刊>Computational Biology and Bioinformatics, IEEE/ACM Transactions on >Constructing Complex 3D Biological Environments from Medical Imaging Using High Performance Computing
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Constructing Complex 3D Biological Environments from Medical Imaging Using High Performance Computing

机译：使用高性能计算从医学影像构建复杂的3D生物环境

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摘要

Extracting information about the structure of biological tissue from static image data is a complex task requiring computationally intensive operations. Here, we present how multicore CPUs and GPUs have been utilized to extract information about the shape, size, and path followed by the mammalian oviduct, called the fallopian tube in humans, from histology images, to create a unique but realistic 3D virtual organ. Histology images were processed to identify the individual cross sections and determine the 3D path that the tube follows through the tissue. This information was then related back to the histology images, linking the 2D cross sections with their corresponding 3D position along the oviduct. A series of linear 2D spline cross sections, which were computationally generated for the length of the oviduct, were bound to the 3D path of the tube using a novel particle system technique that provides smooth resolution of self-intersections. This results in a unique 3D model of the oviduct, which is grounded in reality. The GPU is used for the processor intensive operations of image processing and particle physics based simulations, significantly reducing the time required to generate a complete model.
机译：从静态图像数据中提取有关生物组织结构的信息是一项复杂的任务，需要大量的计算操作。在这里，我们介绍如何利用多核CPU和GPU从组织学图像中提取有关哺乳动物输卵管的形状，大小和路径的信息，该输卵管被称为人类的输卵管，以创建独特而逼真的3D虚拟器官。对组织学图像进行处理以识别各个横截面，并确定试管穿过组织的3D路径。然后将该信息与组织学图像相关联，将2D横截面与沿输卵管的相应3D位置相关联。通过使用一种新颖的粒子系统技术，可为输卵管的长度计算生成一系列线性2D样条曲线横截面，并将其绑定到试管的3D路径上，该技术可提供自相交的平滑分辨率。这样就产生了一个独特的输卵管3D模型，该模型基于现实。 GPU用于图像处理和基于粒子物理学的仿真的处理器密集型操作，从而大大减少了生成完整模型所需的时间。

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