Predicting treatment response from longitudinal images using multi-task deep learning

Radiographic imaging is routinely used to evaluate treatment response in solid tumors. Current imaging response metrics do not reliably predict the underlying biological response. Here, we present a multi-task deep learning approach that allows simultaneous tumor segmentation and response prediction...

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Detalles Bibliográficos
Autores principales: Jin, Cheng, Yu, Heng, Ke, Jia, Ding, Peirong, Yi, Yongju, Jiang, Xiaofeng, Duan, Xin, Tang, Jinghua, Chang, Daniel T., Wu, Xiaojian, Gao, Feng, Li, Ruijiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7994301/
https://www.ncbi.nlm.nih.gov/pubmed/33767170
http://dx.doi.org/10.1038/s41467-021-22188-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7994301/
https://www.ncbi.nlm.nih.gov/pubmed/33767170
http://dx.doi.org/10.1038/s41467-021-22188-y

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