U-Net Architecture for Prostate Segmentation: The Impact of Loss Function on System Performance
Segmentation of the prostate gland from magnetic resonance images is rapidly becoming a standard of care in prostate cancer radiotherapy treatment planning. Automating this process has the potential to improve accuracy and efficiency. However, the performance and accuracy of deep learning models var...
Tallennettuna:
| Päätekijät: | , , , |
|---|---|
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
MDPI AG
2023-03-01
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| Sarja: | Bioengineering |
| Aiheet: | |
| Linkit: | https://www.mdpi.com/2306-5354/10/4/412 |
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