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

Manca Žerovnik Mekuč, Ciril Bohak, Eva Boneš, Samo Hudoklin, Rok Romih, Matija Marolt

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish (US)
Pages (from-to)106959
JournalComputer Methods and Programs in Biomedicine
Volume223
DOIs
StatePublished - Jun 25 2022

ASJC Scopus subject areas

  • Health Informatics
  • Software
  • Computer Science Applications

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