This is an announcement for TrackMate v8.1, an update to the Fiji plugin for cell and organelle tracking in microscopy time-lapse images. The release integrates several major AI-driven detection and tracking algorithms (like Cellpose, Omnipose, YOLO, StarDist, Trackastra) via a reworked, more robust Python integration framework using conda environments. Key improvements also include a comprehensive 2D segmentation editor built on LabKit for manual shape editing and ground-truth generation, support for the new GEFF tracking data exchange format, and enhancements to parameter optimization tools (TrackMate-Helper). The update fixes a long-standing memory leak, which developers maintaining custom modules must be aware of. New users need the latest Fiji version based on Java 8 or newer.
Reviewers for this Topic (Skeptical/Rationalist View):
The people best suited to review this are Computational Biologists/Image Analysis Specialists who are already deep into time-series microscopy data processing and are acutely sensitive to software bugs, integration friction, and algorithmic biases. I'd particularly look for those who value reproducibility and efficiency. Anyone who has spent weeks debugging poorly integrated Python libraries within a Java environment (like Fiji) will offer the most valuable, albeit likely critical, feedback. Developers who have contributed to Fiji plugins or similar open-source projects are also essential due to the API breaking changes noted.
Summary of TrackMate v8.1 Announcement:
TrackMate v8.1 Released (12 December 2025): Latest version of the Fiji plugin for tracking moving objects in time-lapse microscopy data (cells, organelles, particles).
Core Functionality: Detect objects (AI/classical methods), track movement (LAP, Kalman, Trackastra), manually edit results, analyze trajectories, and export data. Handles both simple spots and complex shapes.
Major New Feature: 2D Segmentation Editor (LabKit-based): Allows users to paint and manually edit object shapes directly on 2D images, useful for ground-truth generation or refining automated segmentation. Supports overlapping objects.
Reworked Python Integration: New framework simplifies integrating Python-based AI tools using managed conda environments, improving robustness across OSes.
Developer Note: Integration is significantly accelerated via automated parameter I/O.
GEFF Support: Early support for the new universal tracking data exchange format (developed with multiple collaborators).
Parameter Optimization Tools Updated: TrackMate-Helper rewritten to sweep over detector/tracker parameters, including new SPT/CTC challenge metrics, and incorporating spot/track filters in sweeps. TrackMate-Batcher also updated.
External Viewer: inTRACKtive can now be used as an external browser for large tracking datasets.
Crucial Developer Warning: A long-standing memory leak fix required major API changes. Developers maintaining existing TrackMate modules (detectors/segmenters) will likely see compatibility breaks.
Prerequisite: Users must download the latest Fiji version, as v8.1 is not compatible with older Fiji builds reliant on Java 8.