3DeeCellTracker, a deep learning-based pipeline for segmenting and tracking cells in 3D time lapse images.
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ABSTRACT:
SUBMITTER: Wen C
PROVIDER: S-EPMC8009680 | biostudies-literature | 2021 Mar
REPOSITORIES: biostudies-literature
Publications
3DeeCellTracker, a deep learning-based pipeline for segmenting and tracking cells in 3D time lapse images.
Wen Chentao C Miura Takuya T Voleti Venkatakaushik V Yamaguchi Kazushi K Tsutsumi Motosuke M Yamamoto Kei K Otomo Kohei K Fujie Yukako Y Teramoto Takayuki T Ishihara Takeshi T Aoki Kazuhiro K Nemoto Tomomi T Hillman Elizabeth Mc EM Kimura Koutarou D KD
eLife 20210330
Despite recent improvements in microscope technologies, segmenting and tracking cells in three-dimensional time-lapse images (3D + T images) to extract their dynamic positions and activities remains a considerable bottleneck in the field. We developed a deep learning-based software pipeline, 3DeeCellTracker, by integrating multiple existing and new techniques including deep learning for tracking. With only one volume of training data, one initial correction, and a few parameter changes, 3DeeCell ...[more]
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