Weakly supervised medical image segmentation through dense combinations of dense pseudo-l-abels
Annotating a large amount of medical imaging data thoroughly for training purposes can be expensive, particularly for medical image segmentation tasks; whereas obtaining scribbles, a less precise form of annotation, is more feasible for clinicians. Nevertheless, training semantic segmentation networ...
| Main Authors: | , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Springer
2023
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