Cargando…
Clinical utility of convolutional neural networks for treatment planning in radiotherapy for spinal metastases
BACKGROUND AND PURPOSE: Spine delineation is essential for high quality radiotherapy treatment planning of spinal metastases. However, manual delineation is time-consuming and prone to interobserver variability. Automatic spine delineation, especially using deep learning, has shown promising results...
Autores principales: | Arends, Sebastiaan R.S., Savenije, Mark H.F., Eppinga, Wietse S.C., van der Velden, Joanne M., van den Berg, Cornelis A.T., Verhoeff, Joost J.C. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8857663/ https://www.ncbi.nlm.nih.gov/pubmed/35243030 http://dx.doi.org/10.1016/j.phro.2022.02.003 |
Ejemplares similares
-
A single neural network for cone-beam computed tomography-based radiotherapy of head-and-neck, lung and breast cancer
por: Maspero, Matteo, et al.
Publicado: (2020) -
Does an immobilization mask have added value during planning magnetic resonance imaging for stereotactic radiotherapy of brain tumours?
por: Nagtegaal, Steven H.J., et al.
Publicado: (2020) -
Comparing conVEntional RadioTherapy with stereotactIC body radiotherapy in patients with spinAL metastases: study protocol for an randomized controlled trial following the cohort multiple randomized controlled trial design
por: van der Velden, Joanne M., et al.
Publicado: (2016) -
Stereotactic Radiotherapy Followed by Surgical Stabilization Within 24 h for Unstable Spinal Metastases; A Stage I/IIa Study According to the IDEAL Framework
por: Versteeg, Anne L., et al.
Publicado: (2018) -
Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy
por: Savenije, Mark H. F., et al.
Publicado: (2020)