| Autor: |
Philip M.P. Poortmans, Silvia Takanen, Gustavo Nader Marta, Icro Meattini, Orit Kaidar-Person |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
Breast, Vol 49, Iss , Pp 194-200 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
1532-3080 |
| DOI: |
10.1016/j.breast.2019.11.011 |
| Popis: |
Artificial intelligence demonstrated its value for automated contouring of organs at risk and target volumes as well as for auto-planning of radiation dose distributions in terms of saving time, increasing consistency, and improving dose-volumes parameters. Future developments include incorporating dose/outcome data to optimise dose distributions with optimal coverage of the high-risk areas, while at the same time limiting doses to low-risk areas. An infinite gradient of volumes and doses to deliver spatially-adjusted radiation can be generated, allowing to avoid unnecessary radiation to organs at risk. Therefore, data about patient-, tumour-, and treatment-related factors have to be combined with dose distributions and outcome-containing databases. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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Full Text from ScienceDirect