ITASC

Segment, track, correct, and quantify cells in time-lapse microscopy, inside napari.

ITASC (Interactive Tracking And Segmentation of Cells) takes raw time-lapse stacks to tracked, quantified cells. It segments each frame, links cells across time, lets you correct the result by hand where the automatics miss, and measures what the tracked cells do. It is a napari plugin built for dense, motile monolayers, where segmentation and tracking are the hard part.

What it does

An ITASC run moves through four stages, each usable on its own:

  • Segment each frame with Cellpose-SAM. For sparse, well-separated cells its masks are the result; for a dense monolayer its probability and flow output becomes divergence images that separate crowded, variable-shape cells and form the input the tracker runs on.

  • Track across time: Ultrack for dense monolayers, LapTrack for sparse, well-separated cells.

  • Correct tracks and labels interactively, with editing tools adapted from EpiCure, where the automatic result is wrong.

  • Quantify what the tracked cells do, in two outputs:

    • cell-cell contacts and edges, identified and tracked through T1 transitions, written to a self-describing HDF5 (.h5) file.

    • aggregate analysis of tracked nuclei, cell bodies, and cell-cell contacts (shape and dynamics over time), exported to .csv tables.

How it is organized

ITASC comes in two forms.

The full app is the integrated pipeline. A project is a directory with one subfolder per position, and the four stages hand off through the .tif and HDF5 files on disk, so you can enter wherever your data already sits or pick up a project someone else started.

The solo distributions are separate, smaller napari tools, each built for one job with its own interface: itasc-cellpose segments and tracks channels straight into viewer layers, itasc-tracking turns foreground and contour maps into corrected Ultrack tracks, and itasc-aggregate quantifies contacts and T1 events from finished labels. They are not the full app with stages switched off: each ships only the code its job needs and a leaner interface to match.

Pick the one that matches the data you have. Each row links to that tool’s guide, which covers how to install it and how to use it.

If you have…

Reach for

It gives you

Dense, motile cells of varying shape (a confluent monolayer), from raw stacks to quantified contacts

itasc[all]

The unified ITASC workflow widget, every stage end to end.

Sparse, well-separated cells with a cell and/or nucleus marker, to segment and track one or both channels

itasc-cellpose

A local Cellpose-SAM runner for segmentation, then laptrack linking across time, plus manual correction of tracks and masks (adapted from EpiCure). One channel or two.

Foreground and contour maps already, to skip the cellpose step

itasc-tracking

Ultrack candidate database, solving, browsing, and interactive segmentation and tracking correction.

Tracked cell labels already, and you want the aggregate quantification

itasc-aggregate

Cell-cell edges, border edges, and T1 events to HDF5, aggregate quantification to .csv.

Code to build on

itasc-core

TIFF/path/label-IO helpers, the lineage model, and napari UI primitives.

Built on

ITASC reuses the published methods of four tools. If you use the stage that depends on one, please cite it:

Documentation

  • User guide: install, the staged workflow, and driving the plugin.

  • API reference: the programmatic API, generated from the source.

Status

ITASC is approaching its first public release and JOSS submission. The four stages and the file-based project layout are settled and in active research use. Installation and the public API are close to final: expect small changes before the release and its accompanying manuscript.

Citing ITASC

Cite the software using the metadata in CITATION.cff. A DOI and manuscript citation will be added with the public release. For pre-publication citation questions, contact Artur Ruppel at artur@ruppel.pro.

License

AGPL-3.0. See LICENSE.

AI usage

Generative AI tools (OpenAI GPT and Anthropic Claude) assisted with code drafting, refactoring, tests, debugging, and documentation. Human authors made the scientific, architectural, and design decisions, and are fully responsible for all code and other content in the repository.