Dongheon Lee

585 total citations
27 papers, 397 citations indexed

About

Dongheon Lee is a scholar working on Computer Vision and Pattern Recognition, Surgery and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Dongheon Lee has authored 27 papers receiving a total of 397 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 8 papers in Surgery and 8 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Dongheon Lee's work include Radiomics and Machine Learning in Medical Imaging (5 papers), Surgical Simulation and Training (5 papers) and Colorectal Cancer Screening and Detection (5 papers). Dongheon Lee is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (5 papers), Surgical Simulation and Training (5 papers) and Colorectal Cancer Screening and Detection (5 papers). Dongheon Lee collaborates with scholars based in South Korea, United States and Ethiopia. Dongheon Lee's co-authors include Hee Chan Kim, Hyoun‐Joong Kong, Kyu Eun Lee, Hyeong Won Yu, Hyungju Kwon, Hyungjin Kim, Jin Mo Goo, Eun Hyo Jin, Chang Min Park and Jung Chan Lee and has published in prestigious journals such as Gastroenterology, PLoS ONE and Scientific Reports.

In The Last Decade

Dongheon Lee

23 papers receiving 382 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dongheon Lee South Korea 11 137 128 121 113 89 27 397
Harshawn Malhi United States 10 196 1.4× 96 0.8× 98 0.8× 43 0.4× 67 0.8× 14 439
Christopher P. Bridge United States 14 205 1.5× 81 0.6× 64 0.5× 45 0.4× 80 0.9× 43 593
Marianne Maktabi Germany 15 342 2.5× 182 1.4× 84 0.7× 88 0.8× 230 2.6× 37 555
Petro Kostandy United States 7 218 1.6× 79 0.6× 36 0.3× 33 0.3× 106 1.2× 8 446
Tomas Sakinis Norway 7 265 1.9× 60 0.5× 52 0.4× 35 0.3× 92 1.0× 10 499
Alexandre Moreau–Gaudry France 13 84 0.6× 251 2.0× 213 1.8× 31 0.3× 106 1.2× 43 659
Keewon Shin South Korea 9 199 1.5× 63 0.5× 45 0.4× 64 0.6× 131 1.5× 21 455
Jeevesh Kapur Singapore 12 169 1.2× 76 0.6× 75 0.6× 29 0.3× 69 0.8× 34 477
Archana Laroia United States 12 266 1.9× 87 0.7× 153 1.3× 18 0.2× 28 0.3× 28 513
Jessica H. Nguyen United States 12 86 0.6× 309 2.4× 104 0.9× 36 0.3× 181 2.0× 25 489

Countries citing papers authored by Dongheon Lee

Since Specialization
Citations

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

Fields of papers citing papers by Dongheon Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dongheon Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Dongheon Lee. A scholar is included among the top collaborators of Dongheon Lee 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 Dongheon Lee. Dongheon Lee 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
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2.
Lee, Jong Hyuk, Seung Ho Choi, Hugo J.W.L. Aerts, et al.. (2025). Predicting Respiratory Disease Mortality Risk Using Open-Source AI on Chest Radiographs in an Asian Health Screening Population. Radiology Artificial Intelligence. 7(3). e240628–e240628.
3.
Jang, Seunghyun, et al.. (2025). SeamXSim: Seamless-textured virtual colonoscopy simulator via unpaired long-term video translation. Computers in Biology and Medicine. 198(Pt B). 111217–111217.
4.
5.
Wu, Dufan, Boohwi Hong, Dongheon Lee, et al.. (2024). Texture-preserving low dose CT image denoising using Pearson divergence. Physics in Medicine and Biology. 69(11). 115021–115021. 3 indexed citations
6.
Lee, Jong Hyuk, Dongheon Lee, Michael T. Lu, et al.. (2024). External Testing of a Deep Learning Model to Estimate Biologic Age Using Chest Radiographs. Radiology Artificial Intelligence. 6(5). e230433–e230433. 3 indexed citations
7.
Lee, Dongheon, et al.. (2024). Essential elements of physical fitness analysis in male adolescent athletes using machine learning. PLoS ONE. 19(4). e0298870–e0298870. 6 indexed citations
8.
Lee, Dongheon, et al.. (2023). Optimal view detection for ultrasound-guided supraclavicular block using deep learning approaches. Scientific Reports. 13(1). 17209–17209. 3 indexed citations
9.
Mori, Yuichi, Eun Hyo Jin, & Dongheon Lee. (2023). Enhancing artificial intelligence-doctor collaboration for computer-aided diagnosis in colonoscopy through improved digital literacy. Digestive and Liver Disease. 56(7). 1140–1143. 8 indexed citations
10.
Lee, Jong Hyuk, Dongheon Lee, Michael T. Lu, et al.. (2022). Deep Learning to Optimize Candidate Selection for Lung Cancer CT Screening: Advancing the 2021 USPSTF Recommendations. Radiology. 305(1). 209–218. 21 indexed citations
11.
Lee, Dongheon, et al.. (2022). Feasibility of Measuring Shot Group Using LoRa Technology and YOLO V5. 1–6. 1 indexed citations
12.
Hong, Joonki, Jinhwan Jung, Dongheon Lee, et al.. (2022). End-to-End Sleep Staging Using Nocturnal Sounds from Microphone Chips for Mobile Devices. Nature and Science of Sleep. Volume 14. 1187–1201. 11 indexed citations
13.
Yu, Hyeong Won, Dongheon Lee, Su‐jin Kim, et al.. (2021). Effect of an anti-adhesion agent on vision-based assessment of cervical adhesions after thyroid surgery: randomized, placebo-controlled trial. Scientific Reports. 11(1). 19935–19935. 3 indexed citations
14.
Lee, Dongheon, Hyeong Won Yu, Hyungju Kwon, et al.. (2020). Evaluation of Surgical Skills during Robotic Surgery by Deep Learning-Based Multiple Surgical Instrument Tracking in Training and Actual Operations. Journal of Clinical Medicine. 9(6). 1964–1964. 72 indexed citations
15.
Lee, Dongheon, Woo Hyung Lee, Han Gil Seo, et al.. (2020). Online Learning for the Hyoid Bone Tracking During Swallowing With Neck Movement Adjustment Using Semantic Segmentation. IEEE Access. 8. 157451–157461. 14 indexed citations
16.
Jin, Eun Hyo, Dongheon Lee, Jung Ho Bae, et al.. (2020). Improved Accuracy in Optical Diagnosis of Colorectal Polyps Using Convolutional Neural Networks with Visual Explanations. Gastroenterology. 158(8). 2169–2179.e8. 104 indexed citations
17.
Lee, Dongheon, Hyeong Won Yu, Young Jun Chai, et al.. (2020). Vision-based tracking system for augmented reality to localize recurrent laryngeal nerve during robotic thyroid surgery. Scientific Reports. 10(1). 8437–8437. 22 indexed citations
18.
19.
Kwon, Soon Bin, Seung Min Lee, Dongheon Lee, et al.. (2019). Estimating Maximal Oxygen Uptake From Daily Activity Data Measured by a Watch-Type Fitness Tracker: Cross-Sectional Study. JMIR mhealth and uhealth. 7(6). e13327–e13327. 16 indexed citations
20.
Lee, Dongheon, Hyoun‐Joong Kong, Donguk Kim, et al.. (2018). Preliminary study on application of augmented reality visualization in robotic thyroid surgery. Annals of Surgical Treatment and Research. 95(6). 297–297. 20 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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