Deep learning model for the prediction of lymph node metastasis in esophageal squamous cell carcinoma using MIP FDG-PET images: a retrospective validation study

Hiroki Maruyama, Kentaro Takanami, Eichi Takaya, Shinya Sonobe, Yoshitaka Toyama, Yusuke Taniyama, Chiaki Sato, Hiroshi Okamoto, Yohei Ozawa, Hirotaka Ishida, Kei Takase, Takashi Kamei

Open source

DOI
10.1007/s11604-026-02084-5
Published
2026-09-18
Container
Japanese Journal of Radiology
Publisher
Springer Science and Business Media LLC
Open access
unknown

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BibTeX

@article{allodium:10.1007/s11604-026-02084-5,
  title = {Deep learning model for the prediction of lymph node metastasis in esophageal squamous cell carcinoma using MIP FDG-PET images: a retrospective validation study},
  author = {Hiroki Maruyama and Kentaro Takanami and Eichi Takaya and Shinya Sonobe and Yoshitaka Toyama and Yusuke Taniyama and Chiaki Sato and Hiroshi Okamoto and Yohei Ozawa and Hirotaka Ishida and Kei Takase and Takashi Kamei},
  year = {2026},
  journal = {Japanese Journal of Radiology},
  doi = {10.1007/s11604-026-02084-5},
  url = {https://doi.org/10.1007/s11604-026-02084-5}
}

RIS

TY  - JOUR
TI  - Deep learning model for the prediction of lymph node metastasis in esophageal squamous cell carcinoma using MIP FDG-PET images: a retrospective validation study
AU  - Hiroki Maruyama
AU  - Kentaro Takanami
AU  - Eichi Takaya
AU  - Shinya Sonobe
AU  - Yoshitaka Toyama
AU  - Yusuke Taniyama
AU  - Chiaki Sato
AU  - Hiroshi Okamoto
AU  - Yohei Ozawa
AU  - Hirotaka Ishida
AU  - Kei Takase
AU  - Takashi Kamei
PY  - 2026
JO  - Japanese Journal of Radiology
DO  - 10.1007/s11604-026-02084-5
UR  - https://doi.org/10.1007/s11604-026-02084-5
ER  - 

APA

Maruyama, H., Takanami, K., Takaya, E., Sonobe, S., Toyama, Y., Taniyama, Y., Sato, C., Okamoto, H., Ozawa, Y., Ishida, H., Takase, K., & Kamei, T. (2026). Deep learning model for the prediction of lymph node metastasis in esophageal squamous cell carcinoma using MIP FDG-PET images: a retrospective validation study. Japanese Journal of Radiology. https://doi.org/10.1007/s11604-026-02084-5

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