cells

DAMAN

Component
Description

The method proposed in this paper is a robust combination of multi-task learning and unsupervised domain adaptation for segmenting amoeboid cells in microscopy. This end-to-end framework provides a consolidated mechanism to harness the potential of multi-task learning to isolate and segment clustered cells from low contrast brightfield images, and it simultaneously leverages deep domain adaptation to segment fluorescent cells without explicit pixel-level re- annotation of the data.

The entry-point to the codebase is the main.py file. The user has the option to

  • Train the network on their own dataset
  • Load a pre-trained model and use that for inference on their own data
  • Note: The provided pretrained model was trained on 256x256 images. Results on different resolutions could require fine-tuning This model is trained (supervised) on brightfield, and domain adapted to fluorescence data. The results are saved as 'inference.png'
has topic
Fluorescence microscopy
Bright field microscopy
Machine learning
has function
Cell segmentation
daman

LIVECell

Submitted by Perrine on Tue, 03/28/2023 - 12:31

LIVECell is a manually annotated and expert-validated dataset of 2D phase contrast images, consisting of over 1.6 million cells from a diverse set of cell morphologies and culture densities. It is also associated with some trained models. All are published under CC BY-NC 4.0 license.

Nanotomy: Large-scale electron microscopy (EM) datasets

Submitted by Perrine on Tue, 03/14/2023 - 12:36

Nanotomy shares based on the ATLASTM browser-based viewer from Zeiss. This database allow to browse data set from the publications of Giepmans lab. 

The full list of data set is availble from :

nanotomy.org

Except the papers and where otherwise noted, this work is licensed under a Creative Commons Attribution 4.0 International License

 

Images can be downloaded but only as screenshots (saved as png).

Cell-IDR

Submitted by Perrine on Mon, 03/06/2023 - 16:40

The Image Data Resource (IDR) is a public repository of image datasets from published scientific studies, where the community can submit, search and access high-quality bio-image data. It is part of The BioImage Archive stores and distributes biological images that are useful to life-science researchers. Its development will provide data archiving services to the broader bioimaging database community. This includes added-value bioimaging data resources such as EMPIAR, Cell-IDR and Tissue-IDR.

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