This page describes a detector module for TrackMate that relies on LACSS to segment cells in 2D or 3D. It is not included in the base installation of TrackMate and must be installed via its own update site. Lacss itself is a deep-learning (DL) model for single-cell segmentation from microscopy images.
The design of TrackMate-Lacss follows a server/client architecture, using the GRPC communication protocol. In such case, the Lacss program runs as a GRPC server, listening on a TCP port, which the thin client TrackMate-Lacss uses to communicates with the server, sending the image data and receiving the segmentation results.
By default, Trackmate-Lacss will contact the open server (lacss.cam.uchc.edu) we have setup for this purpose. This simplify the workflow for most users, as they only need to install a small Fiji plugin to fully take advantage of the DL model’s capability. The server-client design allows the user to perform computation quickly on limited hardware resources, becasue most of the computation is done on the server-side.
The user can also setup their own inference server. See section below.
Limitations
3D segmentation results will not be rendered in full. Instead, only a single point per cell will be displayed. This is a limitation of TrackMate itself and will be resolved in the next major release of TrackMate.
Installation
In Fiji, go to Help › Update…, update, and click on (bottom-left). A new window containing all the known update sites will appear. Check the TrackMate-Lacss box, perform update, and restart Fiji.
Usage
Lacss Parameters in the TrackMate UI
Server
The address to the GRPC server in the format of hostname:port. The default is lacss.cam.uchc.edu.
Access token
An optional security token. Only used if you are running your own server.
Minimum Cell Area
The minimum cell area/volume in units of pixels.
Scaling Factor
If not 1, the input image will be resized internally before sent to the model. This is useful if your cell sizes (in pixels) differ significantly from those of the training data.
Score Treshold
Minimum score needed to be considered a valid prediction.
NMS IOU
Lacss is an object detection model, and can detect cells that are right on top of each other. If you want to disable this behavior, set a non-zero IOU threshold to remove overlapping cells.
Multi-Channel
By default the segmentation is performed by considering all channels. Uncheck this to segment on only the first channel.
Running your own server
TrackMate-Lacss runs on a client-server architecture. By default, TrackMate-Lacss will contact the open-server at lacss.cam.uchc.edu:443. But some may want to run your own server (e.g. on your own intranet to improve data transfer speed).
Install Lacss
The short version:
pip install lacss[cuda12]
Slightly longer version: See the Lacss Documentation for more details. We recommend installation on a Linux computer with a dedicated GPU.
Lacss installation is independent of Fiji.
Starting the server
To start Lacss on a remote server:
python -m lacss.deploy.remote_server --modelpath=<path_to_model_file>
The server should print out a randomized token string, which serves as the key for access. You should copy and save it somewhere.
> COPY THE TOKEN BELOW FOR ACCESS.
> =======================================================================
> adK11qJ7-LcnIsFRbcPKy8x46Pz6bxJpsXodOhd4P_k
> =======================================================================
The <path_to_model_file> is the local path to the file that contains the model parameters. See Lacss page for download linkes.
Running a Cellpose server
You can also run a “Lacss” server backed by the cellpose model as its backend. To do that
Install cellpose
In most cases, this is simply
pip install cellpose
But see full documentation for more details.
Install Lacss
pip install lacss
Note that in this case, you do not need the cuda12 option.
Start server
python -m lacss.deploy.cellpose_server
- This plugin and page was adapted from Jean-Yves Tinevez’s Trackmate-Cellpose plugin and wiki page.
- Last updated: July 2024*
