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

Radiographic imaging is routinely used to evaluate treatment response in solid tumors. Here, the authors present a multi-task deep learning approach that allows simultaneous tumor segmentation and response prediction from longitudinal images in a multi-center study on rectal cancer.

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Autores principales: Cheng Jin, Heng Yu, Jia Ke, Peirong Ding, Yongju Yi, Xiaofeng Jiang, Xin Duan, Jinghua Tang, Daniel T. Chang, Xiaojian Wu, Feng Gao, Ruijiang Li
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/e3a87f083cd34359a4b0305fc498f5af
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