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Efficient contour-based annotation by iterative deep learning for organ segmentation from volumetric medical images
PURPOSE: Training deep neural networks usually require a large number of human-annotated data. For organ segmentation from volumetric medical images, human annotation is tedious and inefficient. To save human labour and to accelerate the training process, the strategy of annotation by iterative deep...
| Autores principales: | , , , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9889459/ https://www.ncbi.nlm.nih.gov/pubmed/36048319 http://dx.doi.org/10.1007/s11548-022-02730-z |