This tutorial presents the tracking options available in ImarisCell.
ImarisCell features automated methods to identify, segment, trace, classify and analyze Cell, Nucleus and Vesicle objects in 2D and 3D time-resolved images. The Cell creation wizard has been specifically designed and structured to impose specific biological constraints relevant for tracking analysis. The first part of the Cell creation wizard detects, segments and classifies all pertinent cells and sub-cellular components. The next section of the Cell creation wizard provides the tools to track the newly created objects representing Cell, Nuclei or Vesicles.
Tracking allows individual Cell objects to be traced throughout sequential frames of a time dataset. As a result of tracking, each object has a unique identity and can be used to measure and calculate various statistical outputs related to its travel in 2D/3D+time dimensions.
Tracking options within the creation wizard let you set all required parameters including distances and gap sizes.
The tracking of the Nucleus and Vesicle objects in Imaris is based on the Autoregressive Motion algorithm.
The concept of relative tracking is used to track Nuclei and Vesicles objects within the Cell. Since the Cell object itself can be moving relative to the inertial image reference frame, the tracking of Nuclei and Vesicles is relative to the parent Cell of a specified reference point.
In the Parameters sub-window the user can specify the value of the Max Distance parameter. This parameter defines the maximum distance that a tracked Cell object could possibly move between two consecutive time points. This option prohibits connections between a tracked object and a candidate if the distance between the predicted future position of the object and the candidate position exceeds the maximum allowed distance.
To establish a maximum distance value for the selected Cell object type, choose two time points between the greatest movement of the objects is visible. By measuring this length (using the Line measurement tool), a value for the Max Distance parameter is obtained.
In the Options sub-window you can further adjust the tracking settings by selecting the gap closing algorithm to define the maximum gap size or by selecting the option to fill gaps with detected objects.
Random factors such as noise or inconsistent illumination reflected in the image could interfere with object detection, segmentation and tracking across the time dimension. In case when the object is not correctly segmented between two consecutive time points, the track is broken up and the two track fragments are created instead of a continuous one. To avoid creation of track fragments with gaps between undetected or incorrectly segmented objects, the gap closing algorithm creates tracks that are continuous and not affected by the temporary disappearance of the object.
When the Close gap option is selected, the gap closing algorithm tried to connect the objects associated with the same track. It joins track segments beyond the missing section based on the value entered in the Max Gap Size field. The Max Gap Size defines the maximum number of the consecutive time points that are allowed to be missing in order for a track to be continuous.
If the Fill gaps with all detected objects option is selected, the algorithm performs the optimization of the objects expected position for the particular time point. Then the track is generated by connecting objects assuming their optimized positions.
Once the tracking is complete, the Classify tracks step allows you to exclude tracks that would interfere with the interpretation of results. Here you can filter Cells, Nuclei and Vesicle tracks based on a variety of relevant statistical variables.