Improvement of the model performance by applying additionally the refinement classifier and postprocessing steps
| Data | Precision | Recall | F1-score |
|---|---|---|---|
| Without refinement | 49.62 ± 2.87%, n = 11 | 95.78 ± 0.60%, n = 11 | 64.73 ± 2.32%, n = 11 |
| Without clustering | 78.58 ± 1.17%, n = 11 | 79.02 ± 1.93%, n = 11 | 78.38 ± 1.18%, n = 11 |
| Without size threshold | 71.63 ± 1.12%, n = 11 | 82.78 ± 1.80%, n = 11 | 76.38 ± 0.90%, n = 11 |
| Final | 77.87 ± 1.15%, n = 11 | 82.34 ± 1.87%, n = 11 | 79.63 ± 1.11%, n = 11 |
Performance of the model (precision, recall, and F1-score) on images of hMFBs from chemically-fixed acute hippocampal slices (subset of dataset test final) without refinement classifier, without clustering-based segmentation, without removal of too small clusters, and with all steps included. Data are presented as mean ± SEM.