Segmentation of brain ultrastructures in 3D electron microscopy

Description

White matter datasets: We prepared ten samples from rats' white matter for serial block-face scanning electron microscopy (SBEM) imaging. The SBEM images were acquired simultaneously at two resolutions, low and high resolutions, from the white matter. The low-resolution datasets were acquired at a large field of view, 200 um x 100 um x 65 um, with a voxel size of 50 nm x 50 nm x 50 nm. Two-thirds of the low-resolution images correspond to the corpus callosum and one-third to the cingulum. The high-resolution datasets were acquired at a small field of view, 15 um x 15 um x 15 um, with a voxel size of 15 nm x 15 nm x 50 nm from the corpus callosum. All the images were acquired from the ipsi- and contralateral hemispheres of sham-operated rats (n = 2) and rats with traumatic brain injury (n = 3). The high-resolution datasets were automatically segmented using ACSON pipeline [1] and the low-resolution datasets using DeepACSON pipeline [2]. Gray matter datasets: From three rats, one sham-operated (n = 1) and two with traumatic brain injury (n = 2), we collected two samples per brain: the ipsilateral and contralateral hemispheres of the layer VI of the primary somatosensory cortex. The high-resolution datasets of the somatosensory cortex were acquired at a small field of view, 15 um x 15 um x 15 um, with a voxel size of 15 nm x 15 nm x 50 nm using the SBEM technique. The high-resolution datasets were automatically segmented using gACSON software [4]. Please, find the "README" file for further explaining details of the data. You can find the "Methods" section in [1-4] for details related to SBEM image acquisition and image segmentation pipelines. In case of questions, please contact the corresponding author, Alejandra Sierra. Please cite the datasets as follows: Abdollahzadeh, A., Belevich, I., Jokitalo, E., Tohka, J. & Sierra, A. Segmentation of brain ultrastructures in 3D electron microscopy (2020). https://doi.org/10.23729/bad417ca-553f-4fa6-ae0a-22eddd29a230 [1] Abdollahzadeh, A., Belevich, I., Jokitalo, E., Tohka, J. & Sierra, A. Automated 3D Axonal Morphometry of White Matter. Sci. Reports 9 (1), 6084 (2019). https://doi.org/10.1038/s41598-019-42648-2. [2] Abdollahzadeh, A., Belevich, I., Jokitalo, E., Sierra, A. & Tohka, J. DeepACSON Automated Segmentation of White Matter in 3D Electron Microscopy, Communications Biology 4(1):179 (2021)(Abdollahzadeh et al. 2021). https://doi.org/10.1038/s42003-021-01699-w [3] Abdollahzadeh, A, Sierra, S, & Tohka, J. Cylindrical Shape Decomposition for 3D Segmentation of Tubular Objects, IEEE Access 9: 23979–95 (2021). https://doi.org/10.1109/ACCESS.2021.3056958. [4] Behanova, A, Abdollahzadeh, A, Belevich, I, Jokitalo, E, Sierra, A, & Tohka, J. gACSON Software for Automated Segmentation and Morphology Analyses of Myelinated Axons in 3D Electron Microscopy, Computer Methods and Programs in Biomedicine 220, 106802 (2022), https://doi.org/10.1016/j.cmpb.2022.106802
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Year of publication

2021

Type of data

Authors

A.I. Virtanen -instituutti / Bioteknologia ja molekulaarinen lääketiede

Alejandra Sierra Orcid -palvelun logo - Publisher, Rights holder, Creator, Contributor

Ali Abdollahzadeh Orcid -palvelun logo - Creator, Contributor

Jussi Tohka Orcid -palvelun logo - Creator, Contributor

Eija Jokitalo Orcid -palvelun logo - Creator, Contributor

Ilya Belevich Orcid -palvelun logo - Creator, Contributor

Uppsala University

Andrea Behanova - Contributor

Project

Other information

Fields of science

Computer and information sciences; MEDICAL AND HEALTH SCIENCES; Neurosciences

Language

English

Open access

Open

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

Keywords

Axon, Axon segmentation, Cell segmentation, DeepACSON, Electron microscopy, Myelin, Myelinated axons, SBEM, Segmentation, Traumatic brain injury, Ultrastructure, White matter

Subject headings

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