Evaluation of deep learning methods for parotid gland segmentation from CT images

The segmentation of organs at risk is a crucial and time-consuming step in radiotherapy planning. Good automatic methods can significantly reduce the time clinicians have to spend on this task. Due to its variability in shape and low contrast to surrounding structures, segmenting the parotid gland i...

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Detalles Bibliográficos
Autores principales: Hänsch, Annika, Schwier, Michael, Gass, Tobias, Morgas, Tomasz, Haas, Benjamin, Dicken, Volker, Meine, Hans, Klein, Jan, Hahn, Horst K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2018
Materias:
Special Section on Artificial Intelligence in Medical Imaging
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165912/
https://www.ncbi.nlm.nih.gov/pubmed/30276222
http://dx.doi.org/10.1117/1.JMI.6.1.011005

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165912/
https://www.ncbi.nlm.nih.gov/pubmed/30276222
http://dx.doi.org/10.1117/1.JMI.6.1.011005

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