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Supervised Machine-Learning Enables Segmentation and Evaluation of Heterogeneous Post-treatment Changes in Multi-Parametric MRI of Soft-Tissue Sarcoma
Background: Multi-parametric MRI provides non-invasive methods for response assessment of soft-tissue sarcoma (STS) from non-surgical treatments. However, evaluation of MRI parameters over the whole tumor volume may not reveal the full extent of post-treatment changes as STS tumors are often highly...
Gorde:
| Argitaratua izan da: | Front Oncol |
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| Egile Nagusiak: | , , , , , , , , , |
| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
Frontiers Media S.A.
2019
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| Gaiak: | |
| Sarrera elektronikoa: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6795696/ https://ncbi.nlm.nih.gov/pubmed/31649872 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fonc.2019.00941 |
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