| Dynamic PET image denoising using deep convolutional neural networks without prior training datasets F Hashimoto, H Ohba, K Ote, A Teramoto, H Tsukada IEEE access 7, 96594-96603, 2019 | 113 | 2019 |
| Ultrafast timing enables reconstruction-free positron emission imaging SI Kwon, R Ota, E Berg, F Hashimoto, K Nakajima, I Ogawa, Y Tamagawa, ... Nature photonics 15 (12), 914-918, 2021 | 58 | 2021 |
| 4D deep image prior: dynamic PET image denoising using an unsupervised four-dimensional branch convolutional neural network F Hashimoto, H Ohba, K Ote, A Kakimoto, H Tsukada, Y Ouchi Physics in Medicine & Biology 66 (1), 015006, 2021 | 48 | 2021 |
| Automated segmentation of 2D low-dose CT images of the psoas-major muscle using deep convolutional neural networks F Hashimoto, A Kakimoto, N Ota, S Ito, S Nishizawa Radiological physics and technology 12, 210-215, 2019 | 41 | 2019 |
| Denoising of dynamic sinogram by image guided filtering for positron emission tomography F Hashimoto, H Ohba, K Ote, H Tsukada IEEE Transactions on Radiation and Plasma Medical Sciences 2 (6), 541-548, 2018 | 28 | 2018 |
| 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 | 26 | 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 | 24 | 2022 |
| Deep learning-based attenuation correction for brain PET with various radiotracers F Hashimoto, M Ito, K Ote, T Isobe, H Okada, Y Ouchi Annals of Nuclear Medicine 35, 691-701, 2021 | 21 | 2021 |
| Kinetics-induced block matching and 5-D transform domain filtering for dynamic PET image denoising K Ote, F Hashimoto, A Kakimoto, T Isobe, T Inubushi, R Ota, A Tokui, ... IEEE Transactions on Radiation and Plasma Medical Sciences 4 (6), 720-728, 2020 | 20 | 2020 |
| Compressed-sensing magnetic resonance image reconstruction using an iterative convolutional neural network approach F Hashimoto, K Ote, T Oida, A Teramoto, Y Ouchi Applied Sciences 10 (6), 1902, 2020 | 18 | 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 | 16 | 2022 |
| Deep-learning-based fast TOF-PET image reconstruction using direction information K Ote, F Hashimoto Radiological Physics and Technology 15 (1), 72-82, 2022 | 15 | 2022 |
| A feasibility study on 3D interaction position estimation using deep neural network in Cherenkov-based detector: A Monte Carlo simulation study F Hashimoto, K Ote, R Ota, T Hasegawa Biomedical Physics & Engineering Express 5 (3), 035001, 2019 | 14 | 2019 |
| List-mode PET image reconstruction using deep image prior K Ote, F Hashimoto, Y Onishi, T Isobe, Y Ouchi IEEE Transactions on Medical Imaging, 2023 | 13 | 2023 |
| 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 | 13 | 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 | 6 | 2023 |
| Evaluation of D-isomers of 4-borono-2-18F-fluoro-phenylalanine and O-11C-methyl-tyrosine as brain tumor imaging agents: a comparative PET study with their L … M Kanazawa, S Nishiyama, F Hashimoto, T Kakiuchi, H Tsukada EJNMMI research 8, 1-9, 2018 | 6 | 2018 |
| Basic study on the near-infrared light computed tomography, Development of the experimental systems using a digital single-lens reflex camera S Osawa, C Murata, F Hashimoto, A Teramoto, H Fujita Med. Imag. Inform. Sci 32, 44-47, 2015 | 6 | 2015 |
| Direct positron emission imaging: ultra-fast timing enables reconstruction-free imaging R Ota, SI Kwon, E Berg, F Hashimoto, K Nakajima, I Ogawa, Y Tamagawa, ... arXiv preprint arXiv:2105.05805, 2021 | 5 | 2021 |
| Correction for the influence of cataract on macular pigment measurement by autofluorescence technique using deep learning A Obana, K Ote, F Hashimoto, R Asaoka, Y Gohto, S Okazaki, H Yamada Translational vision science & technology 10 (2), 18-18, 2021 | 5 | 2021 |
Kibo OteCentral Research Laboratory, Hamamatsu Photonics K.K.Verified email at crl.hpk.co.jp
