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全自动分割和重构体式电子显微镜数据中的细胞内区室。

Automatic segmentation and reconstruction of intracellular compartments in volumetric electron microscopy data.

机构信息

Faculty of Computer and Information Science, University of Ljubljana, Večna pot 113, Ljubljana 1000, Slovenia.

Faculty of Computer and Information Science, University of Ljubljana, Večna pot 113, Ljubljana 1000, Slovenia; Visual Computing Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.

出版信息

Comput Methods Programs Biomed. 2022 Aug;223:106959. doi: 10.1016/j.cmpb.2022.106959. Epub 2022 Jun 16.

Abstract

BACKGROUND AND OBJECTIVES

In recent years, electron microscopy is enabling the acquisition of volumetric data with resolving power to directly observe the ultrastructure of intracellular compartments. New insights and knowledge about cell processes that are offered by such data require a comprehensive analysis which is limited by the time-consuming manual segmentation and reconstruction methods.

METHOD

We present methods for automatic segmentation, reconstruction, and analysis of intracellular compartments from volumetric data obtained by the dual-beam electron microscopy. We specifically address segmentation of fusiform vesicles and the Golgi apparatus, reconstruction of mitochondria and fusiform vesicles, and morphological analysis of the reconstructed mitochondria.

RESULTS AND CONCLUSION

Evaluation on the public UroCell dataset demonstrated high accuracy of the proposed methods for segmentation of fusiform vesicles and the Golgi apparatus, as well as for reconstruction of mitochondria and analysis of their shapes, while reconstruction of fusiform vesicles proved to be more challenging. We published an extension of the UroCell dataset with all of the data used in this work, to further contribute to research on automatic analysis of the ultrastructure of intracellular compartments.

摘要

背景与目的

近年来,电子显微镜能够获取具有直接观察细胞内区室超微结构分辨率的容积数据。这些数据为细胞过程提供了新的见解和知识,需要全面的分析,但耗时的手动分割和重建方法对此有所限制。

方法

我们提出了从双束电子显微镜获得的容积数据中自动分割、重建和分析细胞内区室的方法。我们特别针对梭形囊泡和高尔基体的分割、线粒体和梭形囊泡的重建以及重建线粒体的形态分析进行了讨论。

结果与结论

在公开的 UroCell 数据集上的评估表明,所提出的方法在分割梭形囊泡和高尔基体、重建线粒体以及分析其形状方面具有很高的准确性,而重建梭形囊泡则更具挑战性。我们发布了 UroCell 数据集的扩展版本,其中包含了本工作中使用的所有数据,以进一步为自动分析细胞内区室的超微结构的研究做出贡献。

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