M. Yamamuro, Y. Asai, N. Hashimoto, N. Yasuda, H. Kimura, T. Yamada, M. Nemoto, Y. Kimura, H. Handa, H. Yoshida, et al. Utility of U-Net for the objective segmentation of the fibroglandular tissue region on clinical digital mammograms. Biomed. Phys. Eng. Express. 2022. 8. 4. 045016-045016
Takashi Nagaoka, Takenori Kozuka, Takahiro Yamada, Hitoshi Habe, Mitsutaka Nemoto, Masahiro Tada, Koji Abe, Hisashi Handa, Hisashi Yoshida, Kazunari Ishii, et al. A Deep Learning System to Diagnose COVID-19 Pneumonia Using Masked Lung CT Images to Avoid AI-Generated COVID-19 Diagnoses that Include Data Outside the Lungs. Advanced Biomedical Engineering. 2022. 11. 76-86
S. Abe, T. Takagi, S. Torisawa, K. Abe, H. Habe, N. Iguchi, K. Takehara, S. Masuma, H. Yagi, T. Yamaguchi, et al. Development of fish spatio-temporal identifying technology using SegNet in aquaculture net cages. Aquacultural Engineering. 2021. 93. 102146-102146
Ikuto Ogawa, Masayuki Otani, Koji Abe, Nobukazu Iguchi, Hitoshi Habe. Indoor Positioning Method using Time-Series Data of Multiple Human Sensors. 2022 IEEE 8th World Forum on Internet of Things (WF-IoT). 2022. 1-2
M. Yamamuro, Y. Asai, N. Hashimoto, N. Yasuda, H. Kimura, T. Yamada, M. Nemoto, Y. Kimura, H. Handa, H. Yoshida, et al. Robustness of a U-net model for different image processing types in segmentation of the mammary gland region. Proc. SPIE 12286, 16th International Workshop on Breast Imaging. 2022. 122860T
K. Abe, K. Ito, M. Minami. A Feature Value for Measuring Progression of Gastric Atrophy Utilizing the Distribution of Folds in Gastric X-ray Images. Proc. of the 7th IIEEJ International Conference on Image Electronics and Visual Computing. 2021. A6-6
K. Abe, T. Maetani, M. Minami. A Method for Measuring Working Hours of PC Users Working at Home. Proc. of the 7th IIEEJ International Conference on Image Electronics and Visual Computing. 2021. 2021. A1-1
M. Yamamuro, Y. Asai, N. Hashimoto, N. Yasuda, T. Yamada, M. Nemoto, Y. Kimura, H. Handa, H. Yoshida, K. Abe, et al. How to select training data to segment mammary gland region using a deep-learning approach for reliable individualized screening mammography. Proc. of SPIE 11597, Medical Imaging 2021: Computer-Aided Diagnosis. 2021. 11597. 115972V