RT Journal Article
SR Electronic
T1 Bringing TrackMate in the era of machine-learning and deep-learning
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.09.03.458852
DO 10.1101/2021.09.03.458852
A1 Dmitry Ershov
A1 Minh-Son Phan
A1 Joanna W. Pylvänäinen
A1 Stéphane U. Rigaud
A1 Laure Le Blanc
A1 Arthur Charles-Orszag
A1 James R. W. Conway
A1 Romain F. Laine
A1 Nathan H. Roy
A1 Daria Bonazzi
A1 Guillaume Duménil
A1 Guillaume Jacquemet
A1 Jean-Yves Tinevez
YR 2021
UL http://biorxiv.org/content/early/2021/09/03/2021.09.03.458852.abstract
AB TrackMate is an automated tracking software used to analyze bioimages and distributed as a Fiji plugin. Here we introduce a new version of TrackMate rewritten to improve performance and usability, and integrating several popular machine and deep learning algorithms to improve versatility. We illustrate how these new components can be used to efficiently track objects from brightfield and fluorescence microscopy images across a wide range of bio-imaging experiments.Competing Interest StatementThe authors have declared no competing interest.