Use the Clear template instead of explicit CSS
Also, if you look carefully, you will see that there are two splitting events - where a spot seems to divide in two spots in the next frame, one merging event - the opposite, and a gap closing event - where a spot disappear for one frame then reappear a bit further. TrackMate is made to handle these events, and we will see how.
== Starting TrackMate ==
The advantage of this approach is that you load in TrackMate, and everything you need will be loaded and displayed. However, if you need to change the target file or if it cannot be retrieved, you will have to open the TrackMate XML file and edit its 4th line.
== The start panel ==
Defining a smaller area to analyze can be very beneficial to test and inspect for correct parameters, particularly for the segmentation step. In this tutorial, the image is so small and parse that we need not worrying about it. Press the '''Next''' button to step forward.
== Choosing a detector ==
In our case, let us just use the '''Dog detector'''.
== The detector configuration panel ==
In our case, the spots we want to track are about 5 pixels in diameter, so this is what we enter in the corresponding field. We don't need anything else. The '''Sub-pixel localization''' option adds a very little overhead so we can leave it on.
== The detection process ==
== Initial spot filtering ==
In our case, we see from the histogram that we could make sense of this step. There is a big peak at low quality (around a value of 1.2) that contains the majority of spots and is most likely represent spurious spots. So we could put the threshold around let's say 5.5 and probably ending in having only relevant spots. But with less than 10 000 spots, we are very very far from 1 million so we need not to use this trick. Leave the threshold bar close to 0 and proceed to the next step.
So nothing much. Let's carry on.
== Spot filtering ==
Press '''Next''' when you are ready to build tracks with these spots.
== Selecting a simple tracker ==