Deep-learning-based flexible pipeline for segmenting and tracking cells in 3D image time series for whole brain imaging

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View ORCID ProfileChentao Wen, Takuya Miura, Yukako Fujie, Takayuki Teramoto, Takeshi Ishihara, Koutarou D. Kimura

doi: https://doi.org/10.1101/385567

Chentao Wen

1Department of Biological Sciences, Graduate School of Science, Osaka University, Toyonaka, Osaka, Japan

Takuya Miura

1Department of Biological Sciences, Graduate School of Science, Osaka University, Toyonaka, Osaka, Japan

Yukako Fujie

2RIKEN center for Advanced Intelligence Project, Tokyo, Japan

Takayuki Teramoto

3Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan

Takeshi Ishihara

3Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan

Koutarou D. Kimura

1Department of Biological Sciences, Graduate School of Science, Osaka University, Toyonaka, Osaka, Japan

2RIKEN center for Advanced Intelligence Project, Tokyo, Japan

3Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan

Movie S5. Tracked neurons (top) and cell-like regions (bottom) in type 3 dataset.
Movie S4. GCaMP signals in raw images in type 2 dataset
Movie S3. Tracked neurons (top) and cell-like regions (bottom) in type 2 dataset.
Movie S2. GCaMP signals in raw images in type 1 dataset
Movie S1. Tracked neurons (top) and cell-like regions (bottom) in type 1 dataset.