Leonard Sunwoo

1.9k total citations · 1 hit paper
72 papers, 1.2k citations indexed

About

Leonard Sunwoo is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Epidemiology. According to data from OpenAlex, Leonard Sunwoo has authored 72 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Radiology, Nuclear Medicine and Imaging, 29 papers in Pulmonary and Respiratory Medicine and 22 papers in Epidemiology. Recurrent topics in Leonard Sunwoo's work include Acute Ischemic Stroke Management (21 papers), Cerebrovascular and Carotid Artery Diseases (17 papers) and Radiomics and Machine Learning in Medical Imaging (16 papers). Leonard Sunwoo is often cited by papers focused on Acute Ischemic Stroke Management (21 papers), Cerebrovascular and Carotid Artery Diseases (17 papers) and Radiomics and Machine Learning in Medical Imaging (16 papers). Leonard Sunwoo collaborates with scholars based in South Korea, United States and United Kingdom. Leonard Sunwoo's co-authors include Jong Chul Ye, Yoseob Han, Jae Hyoung Kim, Byung Se Choi, Yun Jung Bae, Se Jin Cho, Cheolkyu Jung, Sung Hyun Baik, Kyong Joon Lee and Roh‐Eul Yoo and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Stroke.

In The Last Decade

Leonard Sunwoo

65 papers receiving 1.2k citations

Hit Papers

${k}$ -Space Deep Learning for Accelerated MRI 2019 2026 2021 2023 2019 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. ${k}$ -Space Deep Learning for Accelerated MRI
    2019 219 citations Leonard Sunwoo et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Leonard Sunwoo South Korea 21 695 303 191 180 175 72 1.2k
Michael Perkuhn Germany 16 630 0.9× 165 0.5× 101 0.5× 132 0.7× 185 1.1× 18 958
Thomas C. Booth United Kingdom 20 442 0.6× 185 0.6× 201 1.1× 109 0.6× 93 0.5× 70 996
Hiroyuki Uetani Japan 18 666 1.0× 147 0.5× 217 1.1× 89 0.5× 198 1.1× 89 1.1k
Ramona Woitek Austria 26 1.1k 1.7× 248 0.8× 129 0.7× 123 0.7× 230 1.3× 88 2.0k
Fulvio Zaccagna Italy 22 824 1.2× 497 1.6× 80 0.4× 153 0.8× 258 1.5× 83 1.6k
Rebecca E. Thornhill Canada 25 1.3k 1.8× 798 2.6× 207 1.1× 233 1.3× 284 1.6× 81 2.1k
Estanislao Arana Spain 25 676 1.0× 290 1.0× 221 1.2× 163 0.9× 364 2.1× 112 1.8k
Ananth J. Madhuranthakam United States 25 1.3k 1.9× 315 1.0× 116 0.6× 57 0.3× 129 0.7× 90 1.8k
Christian Federau Switzerland 23 1.2k 1.8× 229 0.8× 92 0.5× 286 1.6× 102 0.6× 63 1.7k
Inpyeong Hwang South Korea 17 511 0.7× 204 0.7× 114 0.6× 142 0.8× 93 0.5× 64 938

Countries citing papers authored by Leonard Sunwoo

Since Specialization
Citations

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

Fields of papers citing papers by Leonard Sunwoo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leonard Sunwoo

This figure shows the co-authorship network connecting the top 25 collaborators of Leonard Sunwoo. A scholar is included among the top collaborators of Leonard Sunwoo 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 Leonard Sunwoo. Leonard Sunwoo 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.
Ryu, Wi‐Sun, et al.. (2025). Segmentation of the Hyperdense Artery Sign on Noncontrast CT in Ischemic Stroke Using Artificial Intelligence. Journal of Clinical Neurology. 21(4). 305–305.
2.
Yum, Kyu Sun, Jong‐Won Chung, Kwang‐Yeol Park, et al.. (2025). A multicenter validation and calibration of automated software package for detecting anterior circulation large vessel occlusion on CT angiography. BMC Neurology. 25(1). 100–100.
3.
Kim, Dongmin, Leonard Sunwoo, Chi Kyung Kim, et al.. (2024). Automated Prediction of Proximal Middle Cerebral Artery Occlusions in Noncontrast Brain Computed Tomography. Stroke. 55(6). 1609–1618. 6 indexed citations
4.
5.
Choi, Dongjun, Leonard Sunwoo, Sung Hyun Baik, et al.. (2024). Automated Detection of Steno-Occlusive Lesion on Time-of-Flight MR Angiography: An Observer Performance Study. American Journal of Neuroradiology. 45(9). 1253–1259. 1 indexed citations
6.
Cho, Se Jin, So Yeong Jeong, Sung Hyun Baik, et al.. (2024). Prediction of treatment response after stereotactic radiosurgery of brain metastasis using deep learning and radiomics on longitudinal MRI data. Scientific Reports. 14(1). 11085–11085. 3 indexed citations
7.
Han, Jung Hoon, Hoyeon Lee, Dongmin Kim, et al.. (2024). Automated identification of thrombectomy amenable vessel occlusion on computed tomography angiography using deep learning. Frontiers in Neurology. 15. 1442025–1442025. 5 indexed citations
8.
Sunwoo, Leonard, Se Jin Cho, Sung Hyun Baik, et al.. (2023). A Nationwide Web-Based Survey of Neuroradiologists’ Perceptions of Artificial Intelligence Software for Neuro-Applications in Korea. Korean Journal of Radiology. 24(5). 454–454. 10 indexed citations
9.
Kim, Tackeun, et al.. (2023). Intracranial steno-occlusive lesion detection on time-of-flight MR angiography using multi-task learning. Computerized Medical Imaging and Graphics. 107. 102220–102220. 2 indexed citations
10.
Lee, Si Un, Han‐Gil Jeong, Youngdeok Kim, et al.. (2023). Long-term outcomes and quantitative radiologic analysis of extracranial–intracranial bypass for hemodynamically compromised chronic large artery occlusive disease. Scientific Reports. 13(1). 3717–3717. 2 indexed citations
11.
Choi, Dongjun, Leonard Sunwoo, Sung‐Hye You, Kyong Joon Lee, & Inseon Ryoo. (2023). Application of symmetry evaluation to deep learning algorithm in detection of mastoiditis on mastoid radiographs. Scientific Reports. 13(1). 5337–5337. 2 indexed citations
12.
Jang, Bum‐Sup, et al.. (2020). Machine Learning Model to Predict Pseudoprogression versus Progression in Glioblastoma: A Multi-institutional Study (KROG 18-07). International Journal of Radiation Oncology*Biology*Physics. 108(3). e742–e742. 1 indexed citations
13.
Jeong, Woo‐Jin, Yun Jung Bae, Hyojin Kim, et al.. (2020). MRI-Based Assessment of the Pharyngeal Constrictor Muscle as a Predictor of Surgical Margin after Transoral Robotic Surgery in HPV-Positive Tonsillar Cancer. American Journal of Neuroradiology. 41(12). 2320–2326. 5 indexed citations
14.
Cho, Se Jin, Byung Se Choi, Yun Jung Bae, et al.. (2020). Diagnostic assessment of magnetic resonance imaging for patients with intralabyrinthine schwannoma: A systematic review. Journal of Neuroradiology. 49(1). 41–46. 1 indexed citations
15.
Jung, Seung Chai, Hyunna Lee, Namkug Kim, et al.. (2019). Fully Automatic Segmentation of Acute Ischemic Lesions on Diffusion-Weighted Imaging Using Convolutional Neural Networks: Comparison with Conventional Algorithms. Korean Journal of Radiology. 20(8). 1275–1275. 40 indexed citations
16.
Jung, Seunguk, Cheolkyu Jung, Jae Hyoung Kim, et al.. (2018). Procedural and clinical outcomes of endovascular recanalization therapy in patients with cancer-related stroke. Interventional Neuroradiology. 24(5). 520–528. 37 indexed citations
17.
Woo, Ho Geol, Leonard Sunwoo, Cheolkyu Jung, et al.. (2017). Feasibility of Permanent Stenting with Solitaire FR as a Rescue Treatment for the Reperfusion of Acute Intracranial Artery Occlusion. American Journal of Neuroradiology. 39(2). 331–336. 26 indexed citations
18.
Sunwoo, Leonard, Young Jae Kim, Kwang Gi Kim, et al.. (2017). Computer-aided detection of brain metastasis on 3D MR imaging: Observer performance study. PLoS ONE. 12(6). e0178265–e0178265. 40 indexed citations
19.
Sunwoo, Leonard, Tae Jin Yun, Sung‐Hye You, et al.. (2016). Differentiation of Glioblastoma from Brain Metastasis: Qualitative and Quantitative Analysis Using Arterial Spin Labeling MR Imaging. PLoS ONE. 11(11). e0166662–e0166662. 56 indexed citations
20.
Sunwoo, Leonard, Seung Hong Choi, Roh‐Eul Yoo, et al.. (2015). Paradoxical perfusion metrics of high-grade gliomas with an oligodendroglioma component: quantitative analysis of dynamic susceptibility contrast perfusion MR imaging. Neuroradiology. 57(11). 1111–1120. 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 Michael Perkuhn Breakdown of academic impact, for papers by Thomas C. Booth Breakdown of academic impact, for papers by Hiroyuki Uetani Breakdown of academic impact, for papers by Ramona Woitek Breakdown of academic impact, for papers by Fulvio Zaccagna Breakdown of academic impact, for papers by Rebecca E. Thornhill Breakdown of academic impact, for papers by Estanislao Arana Breakdown of academic impact, for papers by Ananth J. Madhuranthakam Breakdown of academic impact, for papers by Christian Federau Breakdown of academic impact, for papers by Inpyeong Hwang
Rankless by CCL
2026