3DeeCellTracker, a deep learning-based pipeline for segmenting and tracking cells in 3D time lapse images is a research paper published in eLife (2021). On theSindex it has a DataRank of 0. It has been cited 134 times.
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Japan Society for the Promotion of Science
Grant: KAKENHI JP16H06545
Japan Society for the Promotion of Science
Grant: KAKENHI JP20H05700
Japan Society for the Promotion of Science
Grant: KAKENHI JP18H05135
Japan Society for the Promotion of Science
Grant: KAKENHI JP19K15406
NIH/NINDS
Grant: U01NS094296 UF1NS108213
NIH/NCI
Grant: U01CA236554
National Institutes of Natural Sciences
Grant: 01112002
Grant-in-Aid for Research in Nagoya City University
Grant: 48 1912011 1921102
NIH HHS
Grant: P40 OD010440
NINDS NIH HHS
Grant: UF1 NS108213
NINDS NIH HHS
Grant: U01 NS094296
National Institutes of Health
Grant: 3U01NS094296-02S1
Administrative Supplement to BRAIN grant U01NS094296
National Institutes of Health
Grant: 1P40OD010440-01
Caenorhabditis Genetics Center
National Institutes of Health
Grant: 5U01CA236554-02
Flexible Tools for Pre-Clinical Studies to Answer Key Questions UnderlyingHeavy-Ion Radiotherapy
National Institutes of Health
Grant: 1UF1NS108213-01
SCAPE microscopy for high-speed 3D imaging of cellular function in behaving animals: Continued innovation, optimization, and dissemination
NTT-Kyushu University Collaborative Research Program on Basic Science
RIKEN Center for Advanced Intelligence Project
A program for Leading Graduate Schools entitled 'Interdisciplinary graduate school program for systematic understanding of health and disease'
Fields of Study
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Sustainable Development Goals
Additional file 1 of Toward a more accurate 3D atlas of C. elegans neurons
Additional file 1 of Toward a more accurate 3D atlas of C. elegans neurons
Additional file 1 of Tracking unlabeled cancer cells imaged with low resolution in wide migration chambers via U-NET class-1 probability (pseudofluorescence)
Additional file 1 of Tracking unlabeled cancer cells imaged with low resolution in wide migration chambers via U-NET class-1 probability (pseudofluorescence)
Additional file 2 of Tracking unlabeled cancer cells imaged with low resolution in wide migration chambers via U-NET class-1 probability (pseudofluorescence)
Additional file 2 of Tracking unlabeled cancer cells imaged with low resolution in wide migration chambers via U-NET class-1 probability (pseudofluorescence)
Additional file 3 of Tracking unlabeled cancer cells imaged with low resolution in wide migration chambers via U-NET class-1 probability (pseudofluorescence)
Additional file 3 of Tracking unlabeled cancer cells imaged with low resolution in wide migration chambers via U-NET class-1 probability (pseudofluorescence)
Additional file 4 of Tracking unlabeled cancer cells imaged with low resolution in wide migration chambers via U-NET class-1 probability (pseudofluorescence)
Additional file 4 of Tracking unlabeled cancer cells imaged with low resolution in wide migration chambers via U-NET class-1 probability (pseudofluorescence)
NeuroPAL_ID: (Semi-) automated neuron detection, identification, and activity extraction in images of NeuroPAL.
NeuroPAL_ID: (Semi-) automated neuron detection, identification, and activity extraction in images of NeuroPAL.
NeuroPAL_ID