Name
Title | ||
|---|---|---|
Segmentation evaluation with sparse ground truth data: Simulating true segmentations as perfect/imperfect as those generated by humans |
Abstract | ||
|---|---|---|
•Jointly deals with expense and imprecision issues in generating ground truth (GT).•Manual contouring on sparsely selected slices, resulting in 80-96% workload saving.•Fills segmentations on non-selected slices automatically via algorithms.•Determines optimal sparseness factors with reference to human variability in GT.•Segmentation evaluations by pseudo GT indistinguishable from those via GT. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.media.2021.101980 | Medical Image Analysis |
Keywords | DocType | Volume |
Medical image segmentation,Ground truth generation,Inter-segmenter variability,Segmentation evaluation | Journal | 69 |
ISSN | Citations | PageRank |
1361-8415 | 1 | 0.35 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jieyu Li | 1 | 3 | 4.80 |
| Jayaram K Udupa | 2 | 1 | 0.35 |
| Yubing Tong | 3 | 93 | 22.73 |
| Lisheng Wang | 4 | 12 | 5.33 |
| Drew A Torigian | 5 | 2 | 1.72 |