Yoonmi Hong

2.8k total citations
28 papers, 457 citations indexed

About

Yoonmi Hong is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Surgery. According to data from OpenAlex, Yoonmi Hong has authored 28 papers receiving a total of 457 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Biomedical Engineering and 4 papers in Surgery. Recurrent topics in Yoonmi Hong's work include Advanced Neuroimaging Techniques and Applications (14 papers), Advanced MRI Techniques and Applications (8 papers) and MRI in cancer diagnosis (7 papers). Yoonmi Hong is often cited by papers focused on Advanced Neuroimaging Techniques and Applications (14 papers), Advanced MRI Techniques and Applications (8 papers) and MRI in cancer diagnosis (7 papers). Yoonmi Hong collaborates with scholars based in United States, South Korea and China. Yoonmi Hong's co-authors include Kahp‐Yang Suh, Hong Nam Kim, Sun Min Kim, Pew‐Thian Yap, Dinggang Shen, Ilkyoo Koh, Geng Chen, Pilnam Kim, Ye Wu and Pilnam Kim and has published in prestigious journals such as ACS Nano, Biomaterials and NeuroImage.

In The Last Decade

Yoonmi Hong

27 papers receiving 442 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yoonmi Hong United States 11 153 113 95 68 62 28 457
P.A.J. Ackermans Netherlands 11 235 1.5× 53 0.5× 30 0.3× 65 1.0× 94 1.5× 16 540
Huaiyuan Zheng China 12 222 1.5× 167 1.5× 100 1.1× 139 2.0× 20 0.3× 17 649
Marion Geerligs Netherlands 6 228 1.5× 55 0.5× 30 0.3× 64 0.9× 101 1.6× 11 476
Jinfeng Cao China 9 63 0.4× 140 1.2× 79 0.8× 51 0.8× 8 0.1× 24 378
Alexandre Delalleau France 11 214 1.4× 22 0.2× 39 0.4× 59 0.9× 80 1.3× 21 679
Jun Okamoto Japan 13 250 1.6× 42 0.4× 115 1.2× 103 1.5× 19 0.3× 64 531
Zsuzsanna Püspöki Switzerland 6 119 0.8× 73 0.6× 31 0.3× 37 0.5× 100 1.6× 11 414
Yujin Ahn South Korea 12 200 1.3× 47 0.4× 37 0.4× 17 0.3× 17 0.3× 25 430
Simone Bottan Switzerland 8 183 1.2× 139 1.2× 14 0.1× 55 0.8× 29 0.5× 10 373

Countries citing papers authored by Yoonmi Hong

Since Specialization
Citations

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

Fields of papers citing papers by Yoonmi Hong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yoonmi Hong

This figure shows the co-authorship network connecting the top 25 collaborators of Yoonmi Hong. A scholar is included among the top collaborators of Yoonmi Hong 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 Yoonmi Hong. Yoonmi Hong 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.
Hong, Yoonmi, et al.. (2024). Spherical-deconvolution informed filtering of tractograms changes laterality of structural connectome. NeuroImage. 303. 120904–120904. 2 indexed citations
2.
Chen, Geng, et al.. (2023). Deep learning prediction of diffusion MRI data with microstructure-sensitive loss functions. Medical Image Analysis. 85. 102742–102742. 7 indexed citations
3.
Hong, Yoonmi, Emil Cornea, Jessica B. Girault, et al.. (2023). Structural and functional connectome relationships in early childhood. Developmental Cognitive Neuroscience. 64. 101314–101314. 8 indexed citations
4.
Wu, Ye, Yoonmi Hong, Sahar Ahmad, et al.. (2022). Rapid Diffusion Magnetic Resonance Imaging Using Slice-Interleaved Encoding. Medical Image Analysis. 81. 102548–102548. 2 indexed citations
5.
Wu, Ye, Yoonmi Hong, Sahar Ahmad, & Pew‐Thian Yap. (2021). Active Cortex Tractography. Lecture notes in computer science. 12907. 467–476. 2 indexed citations
6.
Hong, Yoonmi, Sahar Ahmad, Ye Wu, Siyuan Liu, & Pew‐Thian Yap. (2021). Vox2Surf: Implicit Surface Reconstruction from Volumetric Data. Lecture notes in computer science. 12966. 644–653. 2 indexed citations
7.
Chen, Geng, Yoonmi Hong, Yongqin Zhang, et al.. (2020). Estimating Tissue Microstructure with Undersampled Diffusion Data via Graph Convolutional Neural Networks. Lecture notes in computer science. 12267. 280–290. 14 indexed citations
8.
Wu, Ye, Yoonmi Hong, Sahar Ahmad, et al.. (2020). Globally Optimized Super-Resolution of Diffusion MRI Data via Fiber Continuity. Lecture notes in computer science. 12267. 260–269.
9.
Wu, Ye, Yoonmi Hong, Sahar Ahmad, et al.. (2020). Tract Dictionary Learning for Fast and Robust Recognition of Fiber Bundles. Lecture notes in computer science. 12267. 251–259. 9 indexed citations
10.
Hong, Yoonmi, Geng Chen, Pew‐Thian Yap, & Dinggang Shen. (2019). Reconstructing High-Quality Diffusion MRI Data from Orthogonal Slice-Undersampled Data Using Graph Convolutional Neural Networks. Lecture notes in computer science. 11766. 529–537. 6 indexed citations
11.
Wu, Ye, Yoonmi Hong, Yuanjing Feng, Dinggang Shen, & Pew‐Thian Yap. (2019). Mitigating gyral bias in cortical tractography via asymmetric fiber orientation distributions. Medical Image Analysis. 59. 101543–101543. 29 indexed citations
12.
Hong, Yoonmi, Geng Chen, Pew‐Thian Yap, & Dinggang Shen. (2019). Multifold Acceleration of Diffusion MRI via Deep Learning Reconstruction from Slice-Undersampled Data. Lecture notes in computer science. 11492. 530–541. 13 indexed citations
13.
Kim, Jaeil, Yoonmi Hong, Geng Chen, et al.. (2019). Graph-Based Deep Learning for Prediction of Longitudinal Infant Diffusion MRI Data. PubMed. 2019. 133–141. 7 indexed citations
14.
Kwon, Seyong, et al.. (2018). Microfluidic on-chip immunohistochemistry directly from a paraffin-embedded section. Biomicrofluidics. 12(4). 44110–44110. 4 indexed citations
15.
Joo, Hyun‐Woo, Eunkyoung Byun, Mihyun Lee, et al.. (2015). Biofunctionalization via flow shear stress resistant adhesive polysaccharide, hyaluronic acid-catechol, for enhanced in vitro endothelialization. Journal of Industrial and Engineering Chemistry. 34. 14–20. 25 indexed citations
16.
Hong, Yoonmi, et al.. (2013). Effects of Various Extracellular Matrix Proteins on the Growth of HL-1 Cardiomyocytes. Cells Tissues Organs. 198(5). 349–356. 8 indexed citations
17.
Kim, Hong Nam, et al.. (2012). Effect of orientation and density of nanotopography in dermal wound healing. Biomaterials. 33(34). 8782–8792. 129 indexed citations
18.
Hong, Yoonmi, et al.. (2009). The Relationship between Metabolic Syndrome and Periodontal Disease except patients with hypertension and type 2 diabetes mellitus in Korea. Journal of Korean Academy of Oral Health. 33(3). 451–460. 4 indexed citations
19.
Yi, Gihwan, Sang‐Kyu Lee, Yoonmi Hong, et al.. (2004). Use of Pi5(t) markers in marker-assisted selection to screen for cultivars with resistance to Magnaporthe grisea. Theoretical and Applied Genetics. 109(5). 978–985. 47 indexed citations
20.
Poole, Catherine B., et al.. (1993). Recent advances in the application of molecular biology in filariasis.. PubMed. 24 Suppl 2. 55–63. 5 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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