A transformer-based multi-task deep learning model for simultaneous infiltrated brain area identification and segmentation of gliomas

BACKGROUND: The anatomical infiltrated brain area and the boundaries of gliomas have a significant impact on clinical decision making and available treatment options. Identifying glioma-infiltrated brain areas and delineating the tumor manually is a laborious and time-intensive process. Previous dee...

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Detalles Bibliográficos
Autores principales: Li, Yin, Zheng, Kaiyi, Li, Shuang, Yi, Yongju, Li, Min, Ren, Yufan, Guo, Congyue, Zhong, Liming, Yang, Wei, Li, Xinming, Yao, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612240/
https://www.ncbi.nlm.nih.gov/pubmed/37891702
http://dx.doi.org/10.1186/s40644-023-00615-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612240/
https://www.ncbi.nlm.nih.gov/pubmed/37891702
http://dx.doi.org/10.1186/s40644-023-00615-1

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