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Segmentation Evaluation with Sparse Ground Truth Data: Simulating True Segmentations as Perfect/Imperfect as Those Generated by Humans
Fully annotated data sets play important roles in medical image segmentation and evaluation. Expense and imprecision are the two main issues in generating ground truth (GT) segmentations. In this paper, in an attempt to overcome these two issues jointly, we propose a method, named SparseGT, which ex...
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| Izdano u: | Med Image Anal |
|---|---|
| Glavni autori: | , , , , |
| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
2021
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| Teme: | |
| Online pristup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7933105/ https://ncbi.nlm.nih.gov/pubmed/33588116 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.media.2021.101980 |
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