Published October 13, 2024 | Version v4
Dataset Open

BioTISR: a time-lapse biological image dataset for super-resolution microscopy

  • 1. Department of Automation, Tsinghua University

Description

BioTISR is a biological image dataset for super-resolution microscopy, currently including 2D and 3D time-lapse image pairs of low-and-high resolution images of a variety of biology structures, aiming to provide a high-quality dataset of time-lapse biological SR images for the community to spark more developments of computational SR methods.

At present, 2D dataset includes five specimens (clathrin-coated pits, lysosomes, outer mitochondrial membrane, microtubules, and F-actin) acquired with the GI/TIRF-SIM mode and nonlinear SIM mode of our Multi-SIM system, and 3D dataset includes three specimens (outer mitochondrial membrane, microtubules, and F-actin) acquired with 3D-SIM mode of the Multi-SIM system. For each type of specimen and each imaging modality, we acquired the raw data from at least 50 distinct regions-of-interest (ROI). For each ROI, we acquired two (3D data) or three (2D data) groups of N-phase × M-orientation × T-timepoint raw images with a constant exposure time but increasing the excitation light intensity, where (N, M, T) are (3, 3, 20) for TIRF-SIM and GI-SIM, (5, 5, 10) for nonlinear SIM, and (3, 5, 10) for 3D-SIM. Specific imaging conditions and scripts for reading MRC file are provided in Supplement Files.

The BioTISR dataset is related to the following paper:Qiao, C., Liu, S., Wang, Y. et al. A neural network for long-term super-resolution imaging of live cells with reliable confidence quantification. Nat Biotechnol (2025). https://doi.org/10.1038/s41587-025-02553-8, which is an extension of our previously published BioSR dataset (https://www.nature.com/articles/s41592-020-01048-5).

Limited by quota, the original images uploaded in the current 3D dataset are wide-field images obtained after averaging 15 images, where (N, M, T) are (1, 1, 10). We will update them to raw SIM images after the quota is expanded.

2D dataset's url:

https://doi.org/10.5281/zenodo.13843670

3D dataset's urls:

F-actin:

WF input: https://doi.org/10.5281/zenodo.13843673

Raw SIM input:https://doi.org/10.5281/zenodo.13994464

Microtubules:

WF input: https://doi.org/10.5281/zenodo.13932988

Raw SIM input: https://doi.org/10.5281/zenodo.13989327

Mitochondria:

WF input: https://doi.org/10.5281/zenodo.13843183

Raw SIM input: https://doi.org/10.5281/zenodo.14000502

 

Update 2025.5.6

Add optical transfer function(OTF) of the microscopy system and the pixel size of each data to the supplementary files.

Files

Supplementary Files for BioTISR.zip

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Additional details

Related works

Continues
Dataset: 10.6084/m9.figshare.13264793.v9 (DOI)
Is described by
Publication: 10.1101/2024.05.04.592503 (DOI)

References

  • Qiao, C., Li, D., Liu, Y. et al. Rationalized deep learning super-resolution microscopy for sustained live imaging of rapid subcellular processes. Nat Biotechnol 41, 367–377 (2023).
  • Qiao, C., Li, D., Guo, Y. et al. Evaluation and development of deep neural networks for image super-resolution in optical microscopy. Nat Methods 18, 194–202 (2021).