no code implementations • 8 Dec 2023 • Saeko Sasuga, Akira Kudo, Yoshiro Kitamura, Satoshi Iizuka, Edgar Simo-Serra, Atsushi Hamabe, Masayuki Ishii, Ichiro Takemasa
To tackle this, we propose two kinds of approaches of image synthesis-based late stage cancer augmentation and semi-supervised learning which is designed for T-stage prediction.