Explainability and controllability of patient‐specific deep learning with attention‐based augmentation for markerless image‐guided radiotherapy

BACKGROUND: We reported the concept of patient‐specific deep learning (DL) for real‐time markerless tumor segmentation in image‐guided radiotherapy (IGRT). The method was aimed to control the attention of convolutional neural networks (CNNs) by artificial differences in co‐occurrence probability (Co...

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Detalles Bibliográficos
Autores principales: Terunuma, Toshiyuki, Sakae, Takeji, Hu, Yachao, Takei, Hideyuki, Moriya, Shunsuke, Okumura, Toshiyuki, Sakurai, Hideyuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
EMERGING IMAGING AND THERAPY MODALITIES
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10100026/
https://www.ncbi.nlm.nih.gov/pubmed/36354286
http://dx.doi.org/10.1002/mp.16095

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10100026/
https://www.ncbi.nlm.nih.gov/pubmed/36354286
http://dx.doi.org/10.1002/mp.16095

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