Name
Abstract | ||
|---|---|---|
•Counting cells in microscopy images is a crucial step to diagnose many diseases.•Non-trivial patterns induce weak labels in annotation procedures, even with experts.•A two-stage cell counting method for weakly-labeled data settings is proposed.•We localize and score objects to correlate prediction scores and raters’ agreements.Our method achieves lower counting errors across multiple ground-truth settings. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.media.2022.102500 | Medical Image Analysis |
Keywords | DocType | Volume |
Automatic cell counting,Counting with uncertainty,Deep Learning,Biomedical image analysis,Microscopy images,Multi-rater data,Perineuronal nets | Journal | 80 |
ISSN | Citations | PageRank |
1361-8415 | 0 | 0.34 |
References | Authors | |
0 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luca Ciampi | 1 | 0 | 0.34 |
| Fabio Carrara | 2 | 0 | 0.34 |
| Valentino Totaro | 3 | 0 | 0.34 |
| Raffaele Mazziotti | 4 | 0 | 0.34 |
| Leonardo Lupori | 5 | 0 | 0.34 |
| Carlos Santiago | 6 | 0 | 0.34 |
| Giuseppe Amato | 7 | 505 | 106.68 |
| Tommaso Pizzorusso | 8 | 0 | 0.34 |
| Claudio Gennaro | 9 | 0 | 0.34 |