cytobrowser v1.3.3

CytoBrowser

CytoBrowser, a JavaScript and Node.js driven environment for fast and accessible collaborative online visualization, assessment, and annotation of very large microscopy images.

Origintating as a fork^1 of TissUUmaps aimed at Cytology ^1: TissUUmaps originally had a strict "clientside only" policy, which was incompatible with the CytoBrowser collaborative aim. 1. Handling z-stacks (focus stacks), ctrl-scroll on your mouse to focus 2. Multi-user shared view with follow options, also when changing images and annotation layers 3. URL encodes the current view and annotation layer; easy to bookmark views, copy and share 4. Point and region annotations with class label and textual comments 5. Automatic server side storage of annotations; import/export of annotations in JSON format

Example

Branches

Current list of branches:

• master - Main stable branch, official releases are from this branch;
• devel - Main development branch, less stable but more up-to-date;
• devel/multi-image - Work in progress to support multiple layers of images (for correlative multimodal analysis);
• devel/multi-image-autoload-hack - Small add-on to hide images with suffix '_FL', and autoload them together with corresponding non-hidden images with same prefix.

Issues

We aim to support all modern browsers. Since development mostly utilizes the Chrome browser, that one can be expected to give the least troublesome usage experience. Please don't be shy to report issues that you experience.

Citing

If you find the CytoBrowser software useful in your research, please consider citing the following article:

Rydell C and Lindblad J. "CytoBrowser: a browser-based collaborative annotation platform for whole slide images". F1000Research 2021, 10:226 (https://doi.org/10.12688/f1000research.51916.1)

@article{ 10.12688/f1000research.51916.1,
  author = {Rydell, C and Lindblad, J},
  title = {CytoBrowser: a browser-based collaborative annotation platform for whole slide images [version 1; peer review: awaiting peer review]},
  journal = {F1000Research},
  volune = {10},
  year = {2021},
  number = {226},
  doi = {10.12688/f1000research.51916.1}
}

Acknowledgement

This work is supported by: VINNOVA grants 2017-02447, 2020-03611 and 2021-01420, and Swedish Research Council proj. 2017-04385.