Sekeun Kim

558 total citations · 1 hit paper
11 papers, 172 citations indexed

About

Sekeun Kim is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Sekeun Kim has authored 11 papers receiving a total of 172 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cardiology and Cardiovascular Medicine, 8 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Sekeun Kim's work include Radiomics and Machine Learning in Medical Imaging (3 papers), Cardiac Valve Diseases and Treatments (3 papers) and Cardiovascular Function and Risk Factors (3 papers). Sekeun Kim is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (3 papers), Cardiac Valve Diseases and Treatments (3 papers) and Cardiovascular Function and Risk Factors (3 papers). Sekeun Kim collaborates with scholars based in United States, South Korea and Hong Kong. Sekeun Kim's co-authors include Hyuk‐Jae Chang, Yeonyee E. Yoon, Quanzheng Li, Zhengliang Liu, Xiang Li, Aoxiao Zhong, Cheng Chen, Tianming Liu, Pheng‐Ann Heng and Dufan Wu and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Medical Imaging and Physics in Medicine and Biology.

In The Last Decade

Sekeun Kim

11 papers receiving 171 citations

Hit Papers

align trajectories

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.

MA-SAM: Modality-agnostic SAM adaptation for 3D medical image segmentation

2024 71 citations Cheng Chen, Juzheng Miao et al. Medical Image Analysis profile →

Peers

Sekeun Kim

RNMI

CCM

CVPR

AI

PRM

Carlo Biffi United Kingdom

Loïc Le Folgoc United Kingdom

Gary Brahm Canada

Shifeng Zhao China

A Freitas Portugal

Marija Habijan Croatia

Tianming Du China

Florin C. Ghesu United States

Federico Biavati Germany

Yeonggul Jang South Korea

Carlo Biffi United Kingdom

Sekeun Kim

114 ×1.7

RNMI

72 ×1.7

CCM

58 ×1.3

CVPR

30 ×0.9

AI

35 ×1.2

PRM

Citations per year, relative to Sekeun Kim Sekeun Kim (= 1×) peers Carlo Biffi

Countries citing papers authored by Sekeun Kim

Since Specialization

Citations

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

Fields of papers citing papers by Sekeun Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sekeun Kim

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

All Works

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11 of 11 papers shown

1.

Kim, Sekeun, et al.. (2025). Cine cardiac magnetic resonance segmentation using temporal-spatial adaptation of prompt-enabled segment-anything-model: a feasibility study. Journal of Cardiovascular Magnetic Resonance. 27(1). 101909–101909. 1 indexed citations

2.

Kim, Sekeun, Cheng Chen, Hui Ren, et al.. (2025). MediViSTA: Medical Video Segmentation Via Temporal Fusion SAM Adaptation for Echocardiography. IEEE Journal of Biomedical and Health Informatics. 29(12). 8954–8964. 3 indexed citations

3.

Roh, Kangsan, Haobo Li, Rebecca Freeman, et al.. (2025). Exercise‐Induced Cardiac Lymphatic Remodeling Mitigates Inflammation in the Aging Heart. Aging Cell. 24(6). e70043–e70043. 4 indexed citations

4.

Kim, Sekeun, Soon H Song, Cheng Chen, et al.. (2025). EchoFM: Foundation Model for Generalizable Echocardiogram Analysis. IEEE Transactions on Medical Imaging. 44(10). 4049–4062. 2 indexed citations

5.

Chen, Cheng, Juzheng Miao, Dufan Wu, et al.. (2024). MA-SAM: Modality-agnostic SAM adaptation for 3D medical image segmentation. Medical Image Analysis. 98. 103310–103310. 71 indexed citations breakdown →

6.

Kim, Sekeun, Hui Ren, Jiang Hu, et al.. (2024). Assessment of valve regurgitation severity via contrastive learning and multi-view video integration. Physics in Medicine and Biology. 69(4). 45020–45020. 3 indexed citations

7.

Kim, Sekeun, Hyung‐Bok Park, Reza Arsanjani, et al.. (2022). Fully automated quantification of cardiac chamber and function assessment in 2-D echocardiography: clinical feasibility of deep learning-based algorithms. The International Journal of Cardiovascular Imaging. 38(5). 1047–1059. 8 indexed citations

8.

Kim, Sekeun, Byron A. Zambrano, Yeonggul Jang, et al.. (2022). Deep Learning on Multiphysical Features and Hemodynamic Modeling for Abdominal Aortic Aneurysm Growth Prediction. IEEE Transactions on Medical Imaging. 42(1). 196–208. 21 indexed citations

9.

Yoon, Yeonyee E., Sekeun Kim, & Hyuk‐Jae Chang. (2021). Artificial Intelligence and Echocardiography. PubMed. 29(3). 193–193. 28 indexed citations

10.

Kim, Sekeun, et al.. (2019). A Cascaded Two-step Approach For Segmentation of Thoracic Organs.. 2349. 5 indexed citations

11.

Lee, Sang‐Eun, Christopher Nguyen, Hyuk‐Jae Chang, et al.. (2018). Three-dimensional Cardiomyocytes Structure Revealed By Diffusion Tensor Imaging and Its Validation Using a Tissue-Clearing Technique. Scientific Reports. 8(1). 6640–6640. 26 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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