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Possum:一种用于从连续切片进行脑图像三维重建的框架。

Possum-A Framework for Three-Dimensional Reconstruction of Brain Images from Serial Sections.

作者信息

Majka Piotr, Wójcik Daniel K

机构信息

Nencki Institute of Experimental Biology, 3 Pasteur Street, 02-093, Warsaw, Poland.

Department of Physiology, Monash University, Clayton, Victoria, 3800, Australia.

出版信息

Neuroinformatics. 2016 Jul;14(3):265-78. doi: 10.1007/s12021-015-9286-1.

Abstract

Techniques based on imaging serial sections of brain tissue provide insight into brain structure and function. However, to compare or combine them with results from three dimensional imaging methods, reconstruction into a volumetric form is required. Currently, there are no tools for performing such a task in a streamlined way. Here we propose the Possum volumetric reconstruction framework which provides a selection of 2D to 3D image reconstruction routines allowing one to build workflows tailored to one's specific requirements. The main components include routines for reconstruction with or without using external reference and solutions for typical issues encountered during the reconstruction process, such as propagation of the registration errors due to distorted sections. We validate the implementation using synthetic datasets and actual experimental imaging data derived from publicly available resources. We also evaluate efficiency of a subset of the algorithms implemented. The Possum framework is distributed under MIT license and it provides researchers with a possibility of building reconstruction workflows from existing components, without the need for low-level implementation. As a consequence, it also facilitates sharing and data exchange between researchers and laboratories.

摘要

基于对脑组织连续切片成像的技术有助于深入了解大脑的结构和功能。然而,为了将它们与三维成像方法的结果进行比较或结合,需要将其重建为体积形式。目前,还没有以简化方式执行此类任务的工具。在此,我们提出了Possum体积重建框架,该框架提供了一系列从二维到三维的图像重建例程,使用户能够构建符合特定需求的工作流程。主要组件包括使用或不使用外部参考进行重建的例程,以及解决重建过程中遇到的典型问题的方案,例如由于切片变形导致的配准误差传播。我们使用合成数据集和从公开可用资源中获取的实际实验成像数据对该实现进行了验证。我们还评估了所实现算法子集的效率。Possum框架根据麻省理工学院许可协议发布,它为研究人员提供了从现有组件构建重建工作流程的可能性,而无需进行底层实现。因此,它也促进了研究人员和实验室之间的共享和数据交换。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/895c/4896981/2ec4d3948080/12021_2015_9286_Fig1_HTML.jpg

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