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Found 2 papers, 2 papers with code
Weakly-Supervised Cell Tracking via Backward-and-Forward Propagation
We propose a weakly-supervised cell tracking method that can train a convolutional neural network (CNN) by using only the annotation of "cell detection" (i. e., the coordinates of cell positions) without association information, in which cell positions can be easily obtained by nuclear staining.
MPM: Joint Representation of Motion and Position Map for Cell Tracking
Conventional cell tracking methods detect multiple cells in each frame (detection) and then associate the detection results in successive time-frames (association).
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