Yuya Onishi

552 total citations
23 papers, 351 citations indexed

About

Yuya Onishi is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Yuya Onishi has authored 23 papers receiving a total of 351 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Radiology, Nuclear Medicine and Imaging, 10 papers in Radiation and 6 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Yuya Onishi's work include Medical Imaging Techniques and Applications (18 papers), Radiation Detection and Scintillator Technologies (10 papers) and Radiomics and Machine Learning in Medical Imaging (9 papers). Yuya Onishi is often cited by papers focused on Medical Imaging Techniques and Applications (18 papers), Radiation Detection and Scintillator Technologies (10 papers) and Radiomics and Machine Learning in Medical Imaging (9 papers). Yuya Onishi collaborates with scholars based in Japan, United Kingdom and China. Yuya Onishi's co-authors include Fumio Hashimoto, Kibo Ote, Atsushi Teramoto, Hiroshi Fujita, Hiroshi Toyama, Tetsuya Tsukamoto, Kazuyoshi Imaizumi, Kuniaki Saito, R. Ota and Yasuomi Ouchi and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Medical Imaging and Molecular Psychiatry.

In The Last Decade

Yuya Onishi

19 papers receiving 347 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yuya Onishi Japan 11 285 99 74 62 57 23 351
Junshen Xu United States 8 264 0.9× 68 0.7× 46 0.6× 77 1.2× 39 0.7× 13 360
T. Whyntie United Kingdom 6 179 0.6× 111 1.1× 39 0.5× 76 1.2× 44 0.8× 10 408
Haonan Xiao Hong Kong 11 227 0.8× 41 0.4× 61 0.8× 70 1.1× 93 1.6× 23 302
Koen A. J. Eppenhof Netherlands 10 240 0.8× 51 0.5× 59 0.8× 105 1.7× 81 1.4× 11 367
Bartłomiej W. Papież United Kingdom 12 258 0.9× 57 0.6× 44 0.6× 112 1.8× 42 0.7× 38 458
Shizuo Kaji Japan 9 157 0.6× 71 0.7× 74 1.0× 77 1.2× 67 1.2× 40 377
Diksha Sharma United States 10 266 0.9× 117 1.2× 161 2.2× 142 2.3× 51 0.9× 27 377
Taohui Xiao China 7 321 1.1× 36 0.4× 22 0.3× 94 1.5× 27 0.5× 15 383
F. Fauci Italy 13 233 0.8× 223 2.3× 165 2.2× 118 1.9× 93 1.6× 27 522
Donghwi Hwang South Korea 9 484 1.7× 32 0.3× 73 1.0× 236 3.8× 156 2.7× 13 588

Countries citing papers authored by Yuya Onishi

Since Specialization
Citations

This map shows the geographic impact of Yuya Onishi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yuya Onishi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuya Onishi more than expected).

Fields of papers citing papers by Yuya Onishi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yuya Onishi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yuya Onishi. The network helps show where Yuya Onishi may publish in the future.

Co-authorship network of co-authors of Yuya Onishi

This figure shows the co-authorship network connecting the top 25 collaborators of Yuya Onishi. A scholar is included among the top collaborators of Yuya Onishi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yuya Onishi. Yuya Onishi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wakuda, Tomoyasu, Masamichi Yokokura, Yasuhiro Magata, et al.. (2025). α7 nicotinic acetylcholine receptor, activated glia, and cognitive impairment in schizophrenia: a dual-tracer PET study. Molecular Psychiatry. 31(2). 739–748. 1 indexed citations
2.
Onishi, Yuya & R. Ota. (2025). Alleviating the trade-off between coincidence time resolution and sensitivity using scalable TOF-DOI detectors. Physics in Medicine and Biology. 70(6). 65003–65003.
3.
Hashimoto, Fumio, Kibo Ote, Yuya Onishi, et al.. (2025). Exploiting network optimization stability for enhanced PET image denoising using deep image prior. Physics in Medicine and Biology. 70(10). 105019–105019.
4.
Onishi, Yuya & R. Ota. (2024). Theoretical understanding of Compton scattering-based reconstruction-free anatomical imaging method. Physical Review Applied. 22(2). 1 indexed citations
5.
Hashimoto, Fumio, Yuya Onishi, Kibo Ote, et al.. (2024). Deep learning-based PET image denoising and reconstruction: a review. Radiological Physics and Technology. 17(1). 24–46. 31 indexed citations
6.
Hashimoto, Fumio, Yuya Onishi, Kibo Ote, Hideaki Tashima, & Taiga Yamaya. (2024). Two-step optimization for accelerating deep image prior-based PET image reconstruction. Radiological Physics and Technology. 17(3). 776–781.
7.
Hashimoto, Fumio, Yuya Onishi, Kibo Ote, et al.. (2024). Correction to: Deep learning-based PET image denoising and reconstruction: a review. Radiological Physics and Technology. 17(2). 580–580.
8.
Onishi, Yuya, et al.. (2024). Transformer-CNN hybrid network for improving PET time of flight prediction. Physics in Medicine and Biology. 69(11). 115047–115047. 4 indexed citations
9.
Onishi, Yuya, et al.. (2024). Animal PET scanner with a large field of view is suitable for high-throughput scanning of rodents. Annals of Nuclear Medicine. 38(7). 544–552. 3 indexed citations
10.
Ohno, Tomohisa, Yuya Onishi, Takashi Isobe, et al.. (2024). Neural substrates of cough control during coughing. Scientific Reports. 14(1). 758–758. 2 indexed citations
11.
Onishi, Yuya, et al.. (2024). Enhancing Coincidence Time Resolution of PET detectors using short-time Fourier transform and residual neural network. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 1065. 169540–169540. 4 indexed citations
12.
Onishi, Yuya, Fumio Hashimoto, Kibo Ote, & R. Ota. (2023). Whole Reconstruction-Free System Design for Direct Positron Emission Imaging From Image Generation to Attenuation Correction. IEEE Transactions on Medical Imaging. 43(5). 1654–1663. 2 indexed citations
13.
Hashimoto, Fumio, Yuya Onishi, Kibo Ote, Hideaki Tashima, & Taiga Yamaya. (2023). Fully 3D implementation of the end-to-end deep image prior-based PET image reconstruction using block iterative algorithm. Physics in Medicine and Biology. 68(15). 155009–155009. 10 indexed citations
14.
Ote, Kibo, Fumio Hashimoto, Yuya Onishi, Takashi Isobe, & Yasuomi Ouchi. (2023). List-Mode PET Image Reconstruction Using Deep Image Prior. IEEE Transactions on Medical Imaging. 42(6). 1822–1834. 24 indexed citations
15.
Onishi, Yuya, Takashi Isobe, Masanori Ito, et al.. (2022). Performance evaluation of dedicated brain PET scanner with motion correction system. Annals of Nuclear Medicine. 36(8). 746–755. 15 indexed citations
16.
Onishi, Yuya, Fumio Hashimoto, Kibo Ote, & R. Ota. (2022). Unbiased TOF estimation using leading-edge discriminator and convolutional neural network trained by single-source-position waveforms. Physics in Medicine and Biology. 67(4). 04NT01–04NT01. 20 indexed citations
17.
Onishi, Yuya, Fumio Hashimoto, Kibo Ote, et al.. (2021). Anatomical-guided attention enhances unsupervised PET image denoising performance. Medical Image Analysis. 74. 102226–102226. 30 indexed citations
18.
Onishi, Yuya, Atsushi Teramoto, Tetsuya Tsukamoto, et al.. (2020). Investigation of pulmonary nodule classification using multi-scale residual network enhanced with 3DGAN-synthesized volumes. Radiological Physics and Technology. 13(2). 160–169. 15 indexed citations
19.
Onishi, Yuya, Atsushi Teramoto, Tetsuya Tsukamoto, et al.. (2019). Multiplanar analysis for pulmonary nodule classification in CT images using deep convolutional neural network and generative adversarial networks. International Journal of Computer Assisted Radiology and Surgery. 15(1). 173–178. 56 indexed citations
20.
Onishi, Yuya, et al.. (2019). A method for the automated classification of benign and malignant masses on digital breast tomosynthesis images using machine learning and radiomic features. Radiological Physics and Technology. 13(1). 27–36. 34 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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