| Automated pulmonary nodule classification in computed tomography images using a deep convolutional neural network trained by generative adversarial networks Y Onishi, A Teramoto, M Tsujimoto, T Tsukamoto, K Saito, H Toyama, ... BioMed Research International 2019, 6051939, 2019 | 92 | 2019 |
| Multiplanar analysis for pulmonary nodule classification in CT images using deep convolutional neural network and generative adversarial networks Y Onishi, A Teramoto, M Tsujimoto, T Tsukamoto, K Saito, H Toyama, ... International Journal of Computer Assisted Radiology and Surgery 15, 173-178, 2020 | 79 | 2020 |
| A method for the automated classification of benign and malignant masses on digital breast tomosynthesis images using machine learning and radiomic features A Sakai, Y Onishi, M Matsui, H Adachi, A Teramoto, K Saito, H Fujita Radiological Physics and Technology 13, 27-36, 2020 | 39 | 2020 |
| Anatomical-guided attention enhances unsupervised PET image denoising performance Y Onishi, F Hashimoto, K Ote, H Ohba, R Ota, E Yoshikawa, Y Ouchi Medical Image Analysis 74, 102226, 2021 | 30 | 2021 |
| PET image reconstruction incorporating deep image prior and a forward projection model F Hashimoto, K Ote, Y Onishi IEEE Transactions on Radiation and Plasma Medical Sciences 6 (8), 841-846, 2022 | 28 | 2022 |
| List-mode PET image reconstruction using deep image prior K Ote, F Hashimoto, Y Onishi, T Isobe, Y Ouchi IEEE Transactions on Medical Imaging 42 (6), 1822-1834, 2023 | 21 | 2023 |
| Investigation of pulmonary nodule classification using multi-scale residual network enhanced with 3DGAN-synthesized volumes Y Onishi, A Teramoto, M Tsujimoto, T Tsukamoto, K Saito, H Toyama, ... Radiological Physics and Technology 13, 160-169, 2020 | 21 | 2020 |
| Performance evaluation of dedicated brain PET scanner with motion correction system Y Onishi, T Isobe, M Ito, F Hashimoto, T Omura, E Yoshikawa Annals of Nuclear Medicine 36 (8), 746-755, 2022 | 17 | 2022 |
| Unbiased TOF estimation using leading-edge discriminator and convolutional neural network trained by single-source-position waveforms Y Onishi, F Hashimoto, K Ote, R Ota Physics in Medicine & Biology 67 (4), 04NT01, 2022 | 16 | 2022 |
| Fully 3D implementation of the end-to-end deep image prior-based PET image reconstruction using block iterative algorithm F Hashimoto, Y Onishi, K Ote, H Tashima, T Yamaya Physics in Medicine & Biology 68 (15), 155009, 2023 | 10 | 2023 |
| Deep learning-based PET image denoising and reconstruction: a review F Hashimoto, Y Onishi, K Ote, H Tashima, AJ Reader, T Yamaya Radiological physics and technology 17 (1), 24-46, 2024 | 9 | 2024 |
| Self-supervised pre-training for deep image prior-based robust PET image denoising Y Onishi, F Hashimoto, K Ote, K Matsubara, M Ibaraki IEEE Transactions on Radiation and Plasma Medical Sciences 8 (4), 348-356, 2023 | 7 | 2023 |
| Transformer-CNN hybrid network for improving PET time of flight prediction X Feng, A Muhashi, Y Onishi, R Ota, H Liu Physics in Medicine & Biology 69 (11), 115047, 2024 | 1 | 2024 |
| Whole reconstruction-free system design for direct positron emission imaging from image generation to attenuation correction Y Onishi, F Hashimoto, K Ote, R Ota IEEE Transactions on Medical Imaging 43 (5), 1654-1663, 2023 | 1 | 2023 |
| Deep learning PET 画像再構成への招待 橋本二三生， 大西佑弥， 大手希望 Medical Imaging Technology 41 (4-5), 162-170, 2023 | 1 | 2023 |
| Enhancing coincidence time resolution of PET detectors using short-time Fourier transform and residual neural network A Muhashi, X Feng, Y Onishi, R Ota, H Liu Nuclear Instruments and Methods in Physics Research Section A: Accelerators …, 2024 | | 2024 |
| Animal PET scanner with a large field of view is suitable for high-throughput scanning of rodents Y Tomonari, Y Onishi, F Hashimoto, K Ote, T Okamoto, H Ohba Annals of Nuclear Medicine 38, 544-552, 2024 | | 2024 |
| List-Mode PET Image Reconstruction Using Dykstra-Like Splitting K Ote, F Hashimoto, Y Onishi, Y Ouchi arXiv preprint arXiv:2403.00394, 2024 | | 2024 |
| Neural substrates of cough control during coughing T Sugi, T Inubushi, T Ohno, Y Onishi, T Isobe, T Shigematsu, S Hanai, ... Scientific Reports 14 (1), 758, 2024 | | 2024 |
Fumio HashimotoCentral Research Laboratory, Hamamatsu Photonics K.K.在 crl.hpk.co.jp 的电子邮件经过验证
