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Benchmarking of deep learning algorithms for 3D instance segmentation of confocal image datasets

Fig 1

Generic workflow of a DL-based image segmentation pipeline.

The DL network is first trained to produce a semantic segmentation which corresponds as closely as possible to a given ground truth. The trained network is then used to segment unseen images. The resulting semantic segmentation is then further processed to obtain the final instance segmentation. DL, deep learning.

Fig 1

doi: https://doi.org/10.1371/journal.pcbi.1009879.g001