Skip to content, Skip to search


Getting started with TrackMate

13 bytes removed, 10:52, 31 July 2013
Choosing a segmenter
<br style="clear: both" />
== Choosing a segmenter detector ==
[[Image:TrackMate SegmenterChoice.png|right|border|]]
You are now offered to choose a segmentation detection algorithm ("segmenterdetector") amongst the currently implemented ones.
The choice is actually quite limited. Apart from the '''Manual segmentationannotation''', you will find 3 segmentersdetectors, but they are all based on [ LoG (Laplacian of Gaussian) segmentation]. They are described in detail elsewhere, but here is what you need to know.
* The '''Log segmenterdetector''' applies a plain LoG segmentation on the image. All calculations are made in the Fourier space, which makes it optimal for intermediate spot sizes, between ≈5 and ≈20 pixels in diameter.* The '''Dog segmenterdetector''' uses the [ difference of Gaussians] approach to approximate a LoG filter by the difference of 2 Gaussians. Calculations are made in the direct space, and it is optimal for small spot sizes, below ≈5 pixels.* The '''Downsmapled LoG segmenterdetector''' uses the LoG segmenterdetector, but downsizes the image by an integer factor before filtering. This makes it optimal for large spot sizes, above ≈20 pixels in diameter, at the cost of localization precision.
In our case, let us just use the '''Dog segmenterdetector'''.
<br style="clear: both" />
Emailconfirmed, incoming, administrator, uploaders