A deep image-to-image network organ segmentation algorithm for radiation treatment planning: principles and evaluation

BACKGROUND: We describe and evaluate a deep network algorithm which automatically contours organs at risk in the thorax and pelvis on computed tomography (CT) images for radiation treatment planning. METHODS: The algorithm identifies the region of interest (ROI) automatically by detecting anatomical...

Descripción completa

Detalles Bibliográficos
Autores principales: Marschner, Sebastian, Datarb, Manasi, Gaasch, Aurélie, Xu, Zhoubing, Grbic, Sasa, Chabin, Guillaume, Geiger, Bernhard, Rosenman, Julian, Corradini, Stefanie, Niyazi, Maximilian, Heimann, Tobias, Möhler, Christian, Vega, Fernando, Belka, Claus, Thieke, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308364/
https://www.ncbi.nlm.nih.gov/pubmed/35869525
http://dx.doi.org/10.1186/s13014-022-02102-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308364/
https://www.ncbi.nlm.nih.gov/pubmed/35869525
http://dx.doi.org/10.1186/s13014-022-02102-6

Ejemplares similares