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Exploit fully automatic low-level segmented PET data for training high-level deep learning algorithms for the corresponding CT data
We present an approach for fully automatic urinary bladder segmentation in CT images with artificial neural networks in this study. Automatic medical image analysis has become an invaluable tool in the different treatment stages of diseases. Especially medical image segmentation plays a vital role,...
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| Gepubliceerd in: | PLoS One |
|---|---|
| Hoofdauteurs: | , , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
Public Library of Science
2019
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6400332/ https://ncbi.nlm.nih.gov/pubmed/30835746 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0212550 |
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