Radiomics and deep learning models for glioblastoma treatment outcome prediction based on tumor invasion modeling
The findings highlight the potential of biophysical modeling for estimating and incorporating the spread of infiltrating cells into CTV delineation. Further clinical investigations are required to validate the clinical efficacy.
Authors
- Wille Häger (ORCID: https://orcid.org/0000-0002-9330-8332)
- M. Lazzeroni (ORCID: https://orcid.org/0000-0001-6676-508X)
- Mehdi Astaraki (ORCID: https://orcid.org/0000-0001-5125-4682)
- Iuliana Toma-Daşu (ORCID: https://orcid.org/0000-0002-7101-240X)
Institutions
- Stockholm University (SE)
- Karolinska Institutet (SE)
Publication Details
- Journal
- Physica Medica
- Published
- 2024-12-25
- DOI
- https://doi.org/10.1016/j.ejmp.2024.104881
- Citations
- 4
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.62
Funders
- Cancerfonden
- Vetenskapsrådet