Showing 1 - 5 results of 5 for search 'Kento Morita', query time: 0.02s Refine Results
  1. 1
    Semi-automatic design concept of 3D-printed individualized template for interstitial brachytherapy of vaginal tumors

    Semi-automatic design concept of 3D-printed individualized template for interstitial brachytherapy of vaginal tumors by Shuhei Sekii, Kento Morita, Ryuichi Yada, Kayoko Tsujino

    Published 2024-05-01
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  2. 2
    Superovulation with an anti-inhibin monoclonal antibody improves the reproductive performance of rat strains by increasing the pregnancy rate and the litter size

    Superovulation with an anti-inhibin monoclonal antibody improves the reproductive performance of rat strains by increasing the pregnancy rate and the litter size by Keiji Mochida, Kohtaro Morita, Yoshio Sasaoka, Kento Morita, Hitoshi Endo, Ayumi Hasegawa, Masahide Asano, Atsuo Ogura

    Published 2024-04-01
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  3. 3
    Prediction of prognosis using artificial intelligence‐based histopathological image analysis in patients with soft tissue sarcomas

    Prediction of prognosis using artificial intelligence‐based histopathological image analysis in patients with soft tissue sarcomas by Tomohito Hagi, Tomoki Nakamura, Hiroto Yuasa, Katsunori Uchida, Kunihiro Asanuma, Akihiro Sudo, Tetsushi Wakabayahsi, Kento Morita

    Published 2024-05-01
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  4. 4
    Evaluating tubulointerstitial compartments in renal biopsy specimens using a deep learning-based approach for classifying normal and abnormal tubules.

    Evaluating tubulointerstitial compartments in renal biopsy specimens using a deep learning-based approach for classifying normal and abnormal tubules. by Satoshi Hara, Emi Haneda, Masaki Kawakami, Kento Morita, Ryo Nishioka, Takeshi Zoshima, Mitsuhiro Kometani, Takashi Yoneda, Mitsuhiro Kawano, Shigehiro Karashima, Hidetaka Nambo

    Published 2022-01-01
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  5. 5
    Evaluating tubulointerstitial compartments in renal biopsy specimens using a deep learning-based approach for classifying normal and abnormal tubules

    Evaluating tubulointerstitial compartments in renal biopsy specimens using a deep learning-based approach for classifying normal and abnormal tubules by Satoshi Hara, Emi Haneda, Masaki Kawakami, Kento Morita, Ryo Nishioka, Takeshi Zoshima, Mitsuhiro Kometani, Takashi Yoneda, Mitsuhiro Kawano, Shigehiro Karashima, Hidetaka Nambo

    Published 2022-01-01
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