Table 7 Segmentation performance for the FIB-SEM dataset
From: Effective automated pipeline for 3D reconstruction of synapses based on deep learning
Size of pixel | Metrics | Becker [15] | U-Net [23] | F-RCNN + | F-RCNN + | F-RCNN + fusion + |
|---|---|---|---|---|---|---|
overlap | Â | Â | Â | Growing [19] | GrabCut | continuity + GrabCut |
0-pixel | AP | 79.3% | 70.3% | 66.8% | 79.4% | 82.8% |
| Â | F1 | 78.2% | 68.9% | 69.4% | 77.5% | 82.9% |
| Â | Jaccard | 61.5% | 54.1% | 53.5% | 65.2% | 70.9% |
3-pixel | AP | 88.0% | 78.8% | 74.0% | 88.1% | 91.6% |
| Â | F1 | 84.4% | 77.2% | 74.6% | 85.4% | 89.4% |
| Â | Jaccard | 74.6% | 60.9% | 60.2% | 75.7% | 79.6% |
5-pixel | AP | 90.2% | 80.6% | 79.5% | 90.8% | 93.0% |
| Â | F1 | 86.6% | 79.3% | 78.9% | 87.8% | 91.1% |
| Â | Jaccard | 80.3% | 67.5% | 67.7% | 80.6% | 83.7% |