Automatic segmentation of bladder cancer on MRI using a convolutional neural network and reproducibility of radiomics features: a two-center study

Yusaku Moribata, Yasuhisa Kurata*, Mizuho Nishio, Aki Kido, Satoshi Otani, Yuki Himoto, Naoko Nishio, Akihiro Furuta, Hiroyuki Onishi, Kimihiko Masui, Takashi Kobayashi, Yuji Nakamoto

*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

19 Scopus citations

Fingerprint

Dive into the research topics of 'Automatic segmentation of bladder cancer on MRI using a convolutional neural network and reproducibility of radiomics features: a two-center study'. Together they form a unique fingerprint.

Keyphrases

Biochemistry, Genetics and Molecular Biology

Neuroscience

Immunology and Microbiology

Earth and Planetary Sciences