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

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

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.

• Language: English
• Keywords: reconstruction, instance segmentation, electron microscopy, mitochondria, Golgi apparatus, fusiform vesicles, urothelium, deep learning, intracellular compartments
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FRI - Faculty of Computer and Information Science ; MF - Faculty of Medicine
• Publication status: Published
• Publication version: Version of Record
• Year: 2022
• Number of pages: 14 str.
• Numbering: Vol. 223, art. 106959
• PID: 20.500.12556/RUL-137728
• UDC: 004.8:537.533.35
• ISSN on article: 0169-2607
• DOI: 10.1016/j.cmpb.2022.106959
• COBISS.SI-ID: 112962819
• Publication date in RUL: 29.06.2022

ŽEROVNIK MEKUČ, Manca, BOHAK, Ciril, BONEŠ, Eva, HUDOKLIN, Samo, ROMIH, Rok and MAROLT, Matija, 2022, Automatic segmentation and reconstruction of intracellular compartments in volumetric electron microscopy data. Computer methods and programs in biomedicine [online]. 2022. Vol. 223, no. 106959. [Accessed 29 June 2025]. DOI 10.1016/j.cmpb.2022.106959. Retrieved from: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=eng&id=137728

Record is a part of a journal

• Title: Computer methods and programs in biomedicine
• Shortened title: Comput. methods programs biomed.
• Publisher: Elsevier
• ISSN: 0169-2607
• COBISS.SI-ID: 25260032

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Slovenian
• Keywords: mikroskopija, mitohondriji, Golgijev aparat, fuziformni vezikli, urotelij, globoko učenje

Projects

• Funder: ARRS - Slovenian Research Agency
• Project number: P3-0108
• Name: Diferenciacija urotelijskih celic