Journal Article

GSI-2024-00800

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Deep learning-based voxel sampling for particle therapy treatment planning

Quarz, A.GSI* ; Volz, L.GSI* ; Antink, C. H. ; Durante, M.GSI* ; Graeff, C. (Corresponding author)GSI*

2024
IOP Publ. Bristol

This record in other databases:  

Please use a persistent id in citations: doi:10.1088/1361-6560/ad5bba  doi:10.15120/GSI-2024-00800

Keyword(s): Deep Learning (MeSH) ; Radiotherapy Planning, Computer-Assisted: methods (MeSH) ; Humans (MeSH) ; Heavy Ion Radiotherapy: methods (MeSH) ; Head and Neck Neoplasms: radiotherapy (MeSH) ; Head and Neck Neoplasms: diagnostic imaging (MeSH) ; Organs at Risk: radiation effects (MeSH) ; deep-learning ; optimization ; particle therapy ; treatment planning

Note: Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 license.

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Contributing Institute(s):

1. Biophysik (BIO)
2. Collaboration FAIR: BIO (BIO@FAIR)

Research Program(s):

1. 633 - Life Sciences – Building Blocks of Life: Structure and Function (POF4-633) (POF4-633)
2. SUC-GSI-Darmstadt - Strategic university cooperation GSI-TU Darmstadt (SUC-GSI-DA) (SUC-GSI-DA)
3. HITRIplus - Heavy Ion Therapy Research Integration plus (101008548) (101008548)

Experiment(s):

1. no experiment theory work (theory)

Appears in the scientific report 2024

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Database coverage:
; ; ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; Ebsco Academic Search ; Essential Science Indicators ; IF < 5 ; JCR ; National-Konsortium ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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