Novel pre‐spatial data fusion deep learning approach for multimodal volumetric outcome prediction models in radiotherapy
For our OS evaluation, our JEPS fusion architecture achieves better integration of inputs and significantly improves predictive performance over most common multimodal approaches. The JEPS fusion technique is easily applied to any volumetric CNN.
Authors
- Anh Lê (ORCID: https://orcid.org/0000-0003-1970-8781)
- Austin J. Iovoli (ORCID: https://orcid.org/0000-0003-2089-8789)
- Mark Farrugia (ORCID: https://orcid.org/0000-0002-0261-0334)
- Anurag Kumar Singh (ORCID: https://orcid.org/0000-0003-0818-0993)
- John C. Asbach (ORCID: https://orcid.org/0000-0002-7300-5967)
Institutions
- Cedars-Sinai Medical Center (US)
- Roswell Park Comprehensive Cancer Center (US)
- University at Buffalo, State University of New York (US)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-02-10
- DOI
- https://doi.org/10.1002/mp.17672
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.08