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Combining seeded region growing and k-nearest neighbours for the segmentation of routinely acquired spatio-temporal image data
PURPOSE: The acquisition conditions of medical imaging are often precisely defined, leading to a high homogeneity among different data sets. Nonetheless, outliers or artefacts still appear and need to be reliably detected to ensure a reliable diagnosis. Thus, the algorithms need to handle small samp...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589180/ https://www.ncbi.nlm.nih.gov/pubmed/37270742 http://dx.doi.org/10.1007/s11548-023-02951-w |