Hongyoon Choi

3.7k total citations
139 papers, 2.4k citations indexed

About

Hongyoon Choi is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Hongyoon Choi has authored 139 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Radiology, Nuclear Medicine and Imaging, 35 papers in Molecular Biology and 32 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Hongyoon Choi's work include Radiomics and Machine Learning in Medical Imaging (35 papers), Medical Imaging Techniques and Applications (29 papers) and Single-cell and spatial transcriptomics (12 papers). Hongyoon Choi is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (35 papers), Medical Imaging Techniques and Applications (29 papers) and Single-cell and spatial transcriptomics (12 papers). Hongyoon Choi collaborates with scholars based in South Korea, Ethiopia and United States. Hongyoon Choi's co-authors include Dong Soo Lee, Dong Soo Lee, Kwon Joong Na, Seunggyun Ha, Gi Jeong Cheon, Jin Chul Paeng, Keon Wook Kang, Do Won Hwang, June-Key Chung and Hyejin Kang and has published in prestigious journals such as Nucleic Acids Research, PLoS ONE and NeuroImage.

In The Last Decade

Hongyoon Choi

123 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hongyoon Choi South Korea 28 876 798 396 324 299 139 2.4k
Rémy Guillevin France 33 1.3k 1.5× 887 1.1× 654 1.7× 423 1.3× 233 0.8× 108 3.9k
Guido Davidzon United States 26 739 0.8× 815 1.0× 403 1.0× 114 0.4× 241 0.8× 80 2.1k
Kyrre E. Emblem Norway 29 1.4k 1.6× 400 0.5× 268 0.7× 304 0.9× 234 0.8× 92 3.1k
María Martínez-Lage United States 32 772 0.9× 604 0.8× 388 1.0× 257 0.8× 408 1.4× 84 3.4k
Feng Feng China 31 1.1k 1.3× 492 0.6× 984 2.5× 156 0.5× 307 1.0× 222 3.6k
Yinyan Wang China 33 1.2k 1.3× 662 0.8× 700 1.8× 616 1.9× 380 1.3× 145 3.3k
Raymond F. Muzic United States 29 1.4k 1.6× 413 0.5× 326 0.8× 142 0.4× 184 0.6× 98 3.1k
Johan Pallud France 38 1.3k 1.5× 526 0.7× 727 1.8× 298 0.9× 186 0.6× 178 4.7k
Daniel‐Christoph Wagner Germany 24 266 0.3× 377 0.5× 229 0.6× 191 0.6× 359 1.2× 75 2.0k
Pooja Rao United States 10 397 0.5× 663 0.8× 133 0.3× 350 1.1× 79 0.3× 14 1.8k

Countries citing papers authored by Hongyoon Choi

Since Specialization
Citations

This map shows the geographic impact of Hongyoon Choi'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 Hongyoon Choi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hongyoon Choi more than expected).

Fields of papers citing papers by Hongyoon Choi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hongyoon Choi. 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 Hongyoon Choi. The network helps show where Hongyoon Choi may publish in the future.

Co-authorship network of co-authors of Hongyoon Choi

This figure shows the co-authorship network connecting the top 25 collaborators of Hongyoon Choi. A scholar is included among the top collaborators of Hongyoon Choi 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 Hongyoon Choi. Hongyoon Choi 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.
2.
Choi, Hongyoon, et al.. (2025). Empowering PET imaging reporting with retrieval-augmented large language models and reading reports database: a pilot single center study. European Journal of Nuclear Medicine and Molecular Imaging. 52(7). 2452–2462. 2 indexed citations
3.
Jeon, So Yeon, Min Soo Byun, Hye Ji Choi, et al.. (2025). Eligibility for lecanemab and donanemab in Korea under Appropriate Use Recommendations. Alzheimer s & Dementia. 21(11). e70875–e70875.
4.
Park, Ji Yong, Jinyeong Choi, Jin Sil Kim, et al.. (2025). Engineering and evaluation of precision-glycosylated clickable albumin nanoplatform for targeting the tumor microenvironment. Theranostics. 16(3). 1482–1503.
5.
Seok, Jungirl, Hongyoon Choi, Eun Kyung Lee, et al.. (2025). Tumor microenvironment remodeling across thyroid cancer differentiation states revealed by spatial transcriptomics. Cancer Immunology Immunotherapy. 74(12). 357–357.
6.
Choi, Jinyeong, et al.. (2024). Generation of super-resolution images from barcode-based spatial transcriptomics by deep image prior. Cell Reports Methods. 5(1). 100937–100937.
7.
Kang, Seung Kwan, et al.. (2024). Accurate Automated Quantification of Dopamine Transporter PET Without MRI Using Deep Learning-based Spatial Normalization. Nuclear Medicine and Molecular Imaging. 58(6). 354–363.
8.
Choi, Hongyoon, Minseok Suh, Wooil Kwon, et al.. (2024). Prospective Comparison of [18F]FDG and [18F]AIF-FAPI-74 PET/CT in the Evaluation of Potentially Resectable Pancreatic Ductal Adenocarcinoma. Molecular Imaging and Biology. 26(6). 1068–1077. 4 indexed citations
9.
Choi, Hongyoon, et al.. (2024). How to Harness the Power of GPT for Scientific Research: A Comprehensive Review of Methodologies, Applications, and Ethical Considerations. Nuclear Medicine and Molecular Imaging. 58(6). 323–331. 1 indexed citations
10.
Kang, Seung Kwan, Ji Yeon Chung, Seong A. Shin, et al.. (2024). Clinical Performance Evaluation of an Artificial Intelligence-Powered Amyloid Brain PET Quantification Method. Nuclear Medicine and Molecular Imaging. 58(4). 246–254. 4 indexed citations
11.
Hong, Jimin, Matthias Brendel, Kjell Erlandsson, et al.. (2023). Forecasting the Pharmacokinetics With Limited Early Frames in Dynamic Brain PET Imaging Using Neural Ordinary Differential Equation. IEEE Transactions on Radiation and Plasma Medical Sciences. 7(6). 607–617. 3 indexed citations
12.
Choi, Hongyoon, et al.. (2023). Deep Learning-Based Feature Extraction from Whole-Body PET/CT Employing Maximum Intensity Projection Images: Preliminary Results of Lung Cancer Data. Nuclear Medicine and Molecular Imaging. 57(5). 216–222. 8 indexed citations
13.
Bae, Sungwoo, Kwon Joong Na, Jaemoon Koh, et al.. (2022). CellDART: cell type inference by domain adaptation of single-cell and spatial transcriptomic data. Nucleic Acids Research. 50(10). e57–e57. 43 indexed citations
14.
Park, Jun‐Young, Seung Kwan Kang, Donghwi Hwang, et al.. (2022). Automatic Lung Cancer Segmentation in [18F]FDG PET/CT Using a Two-Stage Deep Learning Approach. Nuclear Medicine and Molecular Imaging. 57(2). 86–93. 29 indexed citations
15.
Choi, Hongyoon, et al.. (2021). A Negative Correlation Between Blood Glucose Level and 68 Ga-DOTA-TOC Uptake in the Pancreas Uncinate Process. Nuclear Medicine and Molecular Imaging. 56(1). 52–58. 1 indexed citations
16.
Hwang, Donghwi, Seung Kwan Kang, Kyeong Yun Kim, et al.. (2021). Data-driven respiratory phase-matched PET attenuation correction without CT. Physics in Medicine and Biology. 66(11). 115009–115009. 13 indexed citations
17.
Bae, Sungwoo, Hongyoon Choi, & Dong Soo Lee. (2021). Discovery of molecular features underlying the morphological landscape by integrating spatial transcriptomic data with deep features of tissue images. Nucleic Acids Research. 49(10). e55–e55. 28 indexed citations
18.
Park, Jinsick, Jinsick Park, Min Soo Byun, et al.. (2020). Decreased Alpha Reactivity from Eyes-Closed to Eyes-Open in Non-Demented Older Adults with Alzheimer’s Disease: A Combined EEG and [18F]florbetaben PET Study. Journal of Alzheimer s Disease. 77(4). 1681–1692. 7 indexed citations
19.
Choi, Hongyoon & Kwon Joong Na. (2018). A Risk Stratification Model for Lung Cancer Based on Gene Coexpression Network and Deep Learning. BioMed Research International. 2018. 1–11. 18 indexed citations
20.
Choi, Hongyoon, Ji-In Bang, Gi Jeong Cheon, et al.. (2014). 18F-Fluorodeoxyglucose and 11C-methionine positron emission tomography in relation to methyl-guanine methyltransferase promoter methylation in high-grade gliomas. Nuclear Medicine Communications. 36(3). 211–218. 10 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Rémy Guillevin Breakdown of academic impact, for papers by Guido Davidzon Breakdown of academic impact, for papers by Kyrre E. Emblem Breakdown of academic impact, for papers by María Martínez-Lage Breakdown of academic impact, for papers by Feng Feng Breakdown of academic impact, for papers by Yinyan Wang Breakdown of academic impact, for papers by Raymond F. Muzic Breakdown of academic impact, for papers by Johan Pallud Breakdown of academic impact, for papers by Daniel‐Christoph Wagner Breakdown of academic impact, for papers by Pooja Rao
Rankless by CCL
2026