Napari plugin

We wrapped up most of the functionality in a napari widget. The widget is already installed by default, but you must have napari installed to use it.

To use it, open napari and select the widget from the plugins menu selecting ultrack and then Ultrack from the dropdown menu.

The plugin is built around the concept of a tracking workflow. Any workflow is a sequence of pre-processing steps, segmentation, (candidate segments) linking, and the tracking problem solver. We explain the different workflows in the following sections.

Workflows

The difference between the workflows is the way the user provides the information to the plugin, and the way it processes the information. The remaining steps are the same for all workflows. In that sense, segmentation, linking, and solver are the same for all workflows. For each step, the widget provides direct access to the parameters of the step, and the user can change the parameters to adapt the workflow to the specific problem. We explain how these parameters behave in Configuration docs, and, more specifically, in the Experiment, Linking, and Tracking sections. Every input requested by the plugin should be loaded beforehand as a layer in Napari.

There are three workflows available in the plugin:

• Automatic tracking from image: This workflow is designed to track cells in a sequence of images. It uses classical image processing techniques to detect the cells (foreground) and their possible contours. In this workflow, you can change the parameters of the image processing steps. Refer to the documentation of the functions used in the image processing steps:

  • ultrack.imgproc.detect_foreground()

  • ultrack.imgproc.robust_invert()

• Manual tracking: Since ultrack is designed to work with precomputed cell detection and

  contour detection, this workflow is designed for the situation where the user has already computed the cell detection and the contours of the cells. In this situation, no additional parameter is needed, you only need to provide the cell detection and the contours of the cells.

• Automatic tracking from segmentation labels: This workflow is designed to track cells

  in a sequence of images where the user has already computed the segmentation of the cells. This workflow wraps the function ultrack.utils.labels_to_contours() to compute the foreground and contours of the cells from the segmentation labels, refer to its documentation for additional details.

Flow Field Estimation

Every workflow allows the use of a flow field to improve the tracking of dynamic cells. This method estimates the movement of the cells in the sequence of images through the function ultrack.imgproc.flow.timelapse_flow(). See the documentation of this function for additional details.