TrackMate 7: integrating state-of-the-art segmentation algorithms into tracking pipelines

2022/06/02 by Dmitry Ershov, Minh-Son Phan, Joanna W. Pylvänäinen +10 · 69 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Engineering · #Advanced Vision and Imaging #Cell Image Analysis Techniques #Image Processing Techniques and Applications

paper · doi:10.1038/s41592-022-01507-1

openalex publication_date 2022/06/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/03

Abstract

TrackMate is an automated tracking software used to analyze bioimages and is distributed as a Fiji plugin. Here, we introduce a new version of TrackMate. TrackMate 7 is built to address the broad spectrum of modern challenges researchers face by integrating state-of-the-art segmentation algorithms into tracking pipelines. We illustrate qualitatively and quantitatively that these new capabilities function effectively across a wide range of bio-imaging experiments. TrackMate 7 combines the benefits of machine and deep learning-based image segmentation with accurate object tracking to enable improved 2D and 3D tracking of diverse objects in biological research.

Citations

• Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification
• Cellpose: a generalist algorithm for cellular segmentation

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