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Journal of Neuroscience Methods
|
January 8, 2021
Sequential semi-supervised segmentation for serial electron microscopy image with small number of labels
Eichi Takaya, Yusuke Takeichi, Mamiko Ozaki, et al.
Peerj. Computer Science
|
April 5, 2021
Effects of data count and image scaling on Deep Learning training
Daisuke Hirahara, Eichi Takaya, Taro Takahara, et al.
International Journal of Urology : Official Journal of the Japanese Urological Association
|
September 11, 2024
Monitoring prostate cancer after low-dose-rate hemigland brachytherapy with delta-radiomics of diffusion-weighted magnetic resonance imaging
Kotaro Shimada, Motohiro Fujiwara, Daisuke Hirahara, et al.
Journal of Imaging Informatics in Medicine
|
June 28, 2024
Predicting EGFR Status After Radical Nephrectomy or Partial Nephrectomy for Renal Cell Carcinoma on CT Using a Self-attention-based Model: Variable Vision Transformer (vViT)
Takuma Usuzaki, Ryusei Inamori, Mami Ishikuro, et al.
Nihon Hoshasen Gijutsu Gakkai Zasshi
|
August 23, 2021
[Object Detection Model Utilizing Deep Learning to Identify Retained Surgical Gauze in the Body on Postoperative Radiography: Phantom Study]
Takao Tanuma, Tatsuaki Kobayashi, Eichi Takaya, et al.
JA Clinical Reports
|
October 21, 2025
Prediction of financial deficits of postoperative patients in the intensive care unit using machine learning
Saori Ikumi, Takuya Shiga, Eichi Takaya, et al.
Journal of Imaging Informatics in Medicine
|
May 27, 2025
PlaNet-S: an Automatic Semantic Segmentation Model for Placenta Using U-Net and SegNeXt
Isso Saito, Shinnosuke Yamamoto, Eichi Takaya, et al.
Radiological Physics and Technology
|
November 7, 2022
Deep learning model for breast cancer diagnosis based on bilateral asymmetrical detection (BilAD) in digital breast tomosynthesis images
Daiki Shimokawa, Kengo Takahashi, Daiya Kurosawa, et al.
European Radiology
|
February 24, 2022
Deep learning approach of diffusion-weighted imaging as an outcome predictor in laryngeal and hypopharyngeal cancer patients with radiotherapy-related curative treatment: a preliminary study
Hayato Tomita, Tatsuaki Kobayashi, Eichi Takaya, et al.
Breast Cancer (Tokyo, Japan)
|
March 6, 2024
Deep learning model to predict Ki-67 expression of breast cancer using digital breast tomosynthesis
Ken Oba, Maki Adachi, Tomoya Kobayashi, et al.
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Showing results (1-10 of 30) with videos related to
Sort By:
Page
of 3
Journal of Neuroscience Methods
|
January 8, 2021
Sequential semi-supervised segmentation for serial electron microscopy image with small number of labels
Eichi Takaya, Yusuke Takeichi, Mamiko Ozaki, et al.
Peerj. Computer Science
|
April 5, 2021
Effects of data count and image scaling on Deep Learning training
Daisuke Hirahara, Eichi Takaya, Taro Takahara, et al.
International Journal of Urology : Official Journal of the Japanese Urological Association
|
September 11, 2024
Monitoring prostate cancer after low-dose-rate hemigland brachytherapy with delta-radiomics of diffusion-weighted magnetic resonance imaging
Kotaro Shimada, Motohiro Fujiwara, Daisuke Hirahara, et al.
Journal of Imaging Informatics in Medicine
|
June 28, 2024
Predicting EGFR Status After Radical Nephrectomy or Partial Nephrectomy for Renal Cell Carcinoma on CT Using a Self-attention-based Model: Variable Vision Transformer (vViT)
Takuma Usuzaki, Ryusei Inamori, Mami Ishikuro, et al.
Nihon Hoshasen Gijutsu Gakkai Zasshi
|
August 23, 2021
[Object Detection Model Utilizing Deep Learning to Identify Retained Surgical Gauze in the Body on Postoperative Radiography: Phantom Study]
Takao Tanuma, Tatsuaki Kobayashi, Eichi Takaya, et al.
JA Clinical Reports
|
October 21, 2025
Prediction of financial deficits of postoperative patients in the intensive care unit using machine learning
Saori Ikumi, Takuya Shiga, Eichi Takaya, et al.
Journal of Imaging Informatics in Medicine
|
May 27, 2025
PlaNet-S: an Automatic Semantic Segmentation Model for Placenta Using U-Net and SegNeXt
Isso Saito, Shinnosuke Yamamoto, Eichi Takaya, et al.
Radiological Physics and Technology
|
November 7, 2022
Deep learning model for breast cancer diagnosis based on bilateral asymmetrical detection (BilAD) in digital breast tomosynthesis images
Daiki Shimokawa, Kengo Takahashi, Daiya Kurosawa, et al.
European Radiology
|
February 24, 2022
Deep learning approach of diffusion-weighted imaging as an outcome predictor in laryngeal and hypopharyngeal cancer patients with radiotherapy-related curative treatment: a preliminary study
Hayato Tomita, Tatsuaki Kobayashi, Eichi Takaya, et al.
Breast Cancer (Tokyo, Japan)
|
March 6, 2024
Deep learning model to predict Ki-67 expression of breast cancer using digital breast tomosynthesis
Ken Oba, Maki Adachi, Tomoya Kobayashi, et al.
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of 3