Deep learning based radiomics to predict treatment response using multi-datasets

Deep learning based radiomics to predict treatment response using multi-datasets. Brochet, T., Lapuyade-Lahorgue, J., Huat, A., Thureau, S., Pasquier, D., Gardin, I., Modzelewski, R., Gibon, D., Thariat, J., Grégoire, V., Vera, P., & Ruan, S. In Medical Imaging and Computer-Aided Diagnosis (MICAD), pages 431–440, Singapore, November, 2022.
doi bibtex

@inproceedings{Brochet2022Radiomic,
  title = "Deep learning based radiomics to predict treatment response using multi-datasets",
  author = "Brochet, Thibaud and Lapuyade-Lahorgue, Jérome and Huat, Alexandre and Thureau, Sébastien and Pasquier, David and Gardin, Isabelle and Modzelewski, Romain and Gibon, David and Thariat, Juliette and Grégoire, Vincent and Vera, Pierre and Ruan, Su",
  booktitle = "Medical Imaging and Computer-Aided Diagnosis (MICAD)",
  pages = "431--440",
  year = 2022,
  month = nov,
  address = "Singapore",
  doi = "10.1007/978-981-16-6775-6_35",
}

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