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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.
Weakly Supervised Cell Instance Segmentation by Propagating from Detection Response
In addition, we demonstrated that our method can perform without any annotation by using fluorescence images that cell nuclear were stained as training data.
Cell Segmentation
Cultural Vocal Bursts Intensity Prediction
+2
