Jeongjin Lee

3.2k total citations
127 papers, 1.4k citations indexed

About

Jeongjin Lee is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, Jeongjin Lee has authored 127 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Computer Vision and Pattern Recognition, 34 papers in Radiology, Nuclear Medicine and Imaging and 32 papers in Surgery. Recurrent topics in Jeongjin Lee's work include Medical Image Segmentation Techniques (32 papers), Organ Transplantation Techniques and Outcomes (24 papers) and Liver Disease and Transplantation (22 papers). Jeongjin Lee is often cited by papers focused on Medical Image Segmentation Techniques (32 papers), Organ Transplantation Techniques and Outcomes (24 papers) and Liver Disease and Transplantation (22 papers). Jeongjin Lee collaborates with scholars based in South Korea, United States and Canada. Jeongjin Lee's co-authors include Yeong-Gil Shin, Taeyong Park, Namkug Kim, Kyung Won Kim, Yeong Gil Shin, Juneseuk Shin, Kyoung Ho Lee, Kyoung Won Kim, Sung‐Gyu Lee and Hyung Jin Won and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Radiology.

In The Last Decade

Jeongjin Lee

113 papers receiving 1.4k citations

Peers

Jeongjin Lee

RNMI

CVPR

SURGE

HEPAT

Jing Han China

Gabriel Chartrand Canada

Steven C. Horii United States

Sara Moccia Italy

Premal A. Patel United Kingdom

Andrea Schenk Germany

Xiangrong Zhou Japan

Ivo Wolf Germany

Marius George Linguraru United States

Phillip M. Cheng United States

Jing Han China

Jeongjin Lee

350 ×1.0

RNMI

199 ×0.7

CVPR

244 ×0.9

SURGE

151 ×0.7

HEPAT

110 ×0.5

Citations per year, relative to Jeongjin Lee Jeongjin Lee (= 1×) peers Jing Han

Countries citing papers authored by Jeongjin Lee

Since Specialization

Citations

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

Fields of papers citing papers by Jeongjin Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeongjin Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Jeongjin Lee. A scholar is included among the top collaborators of Jeongjin 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 Jeongjin Lee. Jeongjin Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Lee, Jeongjin, et al.. (2024). Censored broken adaptive ridge regression in high-dimension. Computational Statistics. 39(6). 3457–3482. 2 indexed citations

Park, Taeyong, Chin Su Koh, Myung Ji Kim, et al.. (2023). Simulation Method for the Physical Deformation of a Three-Dimensional Soft Body in Augmented Reality-Based External Ventricular Drainage. Healthcare Informatics Research. 29(3). 218–227.

Kim, Dong Wook, Kyung Won Kim, Seung Soo Lee, et al.. (2022). Prognostic Value of Sarcopenia and Myosteatosis in Patients with Resectable Pancreatic Ductal Adenocarcinoma. Korean Journal of Radiology. 23(11). 1055–1055. 23 indexed citations

Lee, Sunyoung, Kyoung Won Kim, Heon‐Ju Kwon, et al.. (2022). Impact of the preoperative skeletal muscle index on early remnant liver regeneration in living donors after liver transplantation. SHILAP Revista de lepidopterología. 36(4). 259–266.

Kim, Dong Wook, Jiyeon Ha, Yousun Ko, et al.. (2021). Reliability of Skeletal Muscle Area Measurement on CT with Different Parameters: A Phantom Study. Korean Journal of Radiology. 22(4). 624–624. 24 indexed citations

Kim, Dong Wook, Kyung Won Kim, Yousun Ko, et al.. (2021). Effects of Contrast Phases on Automated Measurements of Muscle Quantity and Quality Using CT. Korean Journal of Radiology. 22(11). 1909–1909. 6 indexed citations

Yoon, Ja Kyung, Sunyoung Lee, Kyung Won Kim, et al.. (2021). Reference Values for Skeletal Muscle Mass at the Third Lumbar Vertebral Level Measured by Computed Tomography in a Healthy Korean Population. Endocrinology and Metabolism. 36(3). 672–677. 15 indexed citations

Park, Taeyong, et al.. (2020). Accurate face registration for 3D surgical navigation system. 16(1). 30–42. 1 indexed citations

Kim, Dong Wook, Kyung Won Kim, Yousun Ko, et al.. (2020). Assessment of Myosteatosis on Computed Tomography by Automatic Generation of a Muscle Quality Map Using a Web-Based Toolkit: Feasibility Study. JMIR Medical Informatics. 8(10). e23049–e23049. 34 indexed citations

10.

Lee, Jeongjin, et al.. (2020). Confidence-Controlled Local Isosurfacing. IEEE Transactions on Visualization and Computer Graphics. 27(1). 29–42. 2 indexed citations

11.

Park, Taeyong, et al.. (2019). Rapid and Accurate Registration Method between Intraoperative 2D XA and Preoperative 3D CTA Images for Guidance of Percutaneous Coronary Intervention. Computational and Mathematical Methods in Medicine. 2019. 1–12. 3 indexed citations

12.

Park, Hyo Jung, Youngbin Shin, Jisuk Park, et al.. (2019). Development and Validation of a Deep Learning System for Segmentation of Abdominal Muscle and Fat on Computed Tomography. Korean Journal of Radiology. 21(1). 88–88. 97 indexed citations

13.

Lee, Min-Kyung, et al.. (2018). Deeply Self-Supervising Edge-to-Contour Neural Network Applied to Liver Segmentation.. arXiv (Cornell University). 2 indexed citations

14.

Lee, Jeongjin, et al.. (2017). Technology opportunity discovery to R&D planning: Key technological performance analysis. Technological Forecasting and Social Change. 119. 53–63. 33 indexed citations

15.

Kang, Ho Chul, et al.. (2015). Fast and Accurate Semiautomatic Segmentation of Individual Teeth from Dental CT Images. Computational and Mathematical Methods in Medicine. 2015. 1–12. 12 indexed citations

16.

Park, Seongjin, Jeongjin Lee, Hyunna Lee, et al.. (2014). Parallelized Seeded Region Growing Using CUDA. Computational and Mathematical Methods in Medicine. 2014. 1–10. 5 indexed citations

17.

Lee, Jeongjin, et al.. (2010). 3D Cloud Animation using Cloud Modeling Method of 2D Meteorological Satellite Images. Journal of Korea Game Society. 10(1). 147–156.

18.

Lee, Jeongjin, Jong-Ho Kim, & Taeyoung Kim. (2010). Fingertip Extraction and Hand Motion Recognition Method for Augmented Reality Applications. Journal of Korea Multimedia Society. 13(2). 316–323. 3 indexed citations

19.

Lee, Jeongjin, et al.. (2010). A Phenomenological Studies on Ignition Characteristics of Wires by Local Impact, Over Loading and Overcurrent. 12(4). 53–60. 1 indexed citations

20.

Lee, Jeongjin, et al.. (1986). Public and Experts Perception about Nanotechnology Hazards in Korea. 23(4). 247–256. 2 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