Cell segmentation and tracking using CNN-based distance predictions and a graph-based matching strategy
Fig 2
Overview of the proposed segmentation method using distance predictions (adapted from [13]).
The CNN consists of a single encoder that is connected to both decoder paths. The network is trained to predict cell distances and neighbor distances that are used for the watershed-based post-processing. The input image shows a crop of the Cell Tracking Challenge data set Fluo-N2DH-GOWT1 [7, 9].