Jaewon Yang

4.9k total citations · 3 hit papers
51 papers, 3.2k citations indexed

About

Jaewon Yang is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Biomedical Engineering. According to data from OpenAlex, Jaewon Yang has authored 51 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Radiology, Nuclear Medicine and Imaging, 15 papers in Radiation and 12 papers in Biomedical Engineering. Recurrent topics in Jaewon Yang's work include Medical Imaging Techniques and Applications (36 papers), Advanced MRI Techniques and Applications (14 papers) and Radiomics and Machine Learning in Medical Imaging (12 papers). Jaewon Yang is often cited by papers focused on Medical Imaging Techniques and Applications (36 papers), Advanced MRI Techniques and Applications (14 papers) and Radiomics and Machine Learning in Medical Imaging (12 papers). Jaewon Yang collaborates with scholars based in United States, Australia and India. Jaewon Yang's co-authors include Jure Leskovec, Youngho Seo, Thomas A. Hope, Peder E. Z. Larson, Quanzheng Li, Kuang Gong, Dattesh Shanbhag, Florian Wiesinger, Sandeep Kaushik and Georges El Fakhri and has published in prestigious journals such as Scientific Reports, Radiology and Magnetic Resonance in Medicine.

In The Last Decade

Jaewon Yang

47 papers receiving 3.1k 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.

Defining and evaluating network communities based on ground-truth

2013 894 citations Jaewon Yang et al. profile →
Overlapping community detection at scale

2013 535 citations Jaewon Yang et al. profile →
Defining and evaluating network communities based on ground-truth

2012 464 citations Jaewon Yang et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jaewon Yang United States	19	1.7k	1.1k	886	597	520	51	3.2k
Xiaoping Yang China	29	450 0.3×	397 0.4×	528 0.6×	183 0.3×	723 1.4×	262	3.6k
Liang Zhao Brazil	25	1.4k 0.8×	861 0.8×	120 0.1×	728 1.2×	489 0.9×	215	2.9k
Wei Lu Singapore	33	952 0.6×	3.9k 3.7×	42 0.0×	199 0.3×	561 1.1×	127	4.9k
Zhong Liu China	29	877 0.5×	422 0.4×	32 0.0×	657 1.1×	253 0.5×	297	3.3k
Daniel Boley United States	26	408 0.2×	964 0.9×	95 0.1×	230 0.4×	731 1.4×	117	3.0k
Marco Pellegrini Italy	24	155 0.1×	1.1k 1.0×	657 0.7×	121 0.2×	392 0.8×	107	2.9k
Marco Brambilla Italy	33	128 0.1×	1.0k 1.0×	112 0.1×	451 0.8×	160 0.3×	252	4.3k
Anke Meyer‐Baese United States	27	183 0.1×	784 0.7×	705 0.8×	449 0.8×	268 0.5×	193	2.3k
Amlan Chakrabarti India	24	296 0.2×	916 0.9×	199 0.2×	193 0.3×	383 0.7×	317	2.8k
Di Jin China	27	110 0.1×	1.3k 1.2×	218 0.2×	58 0.1×	289 0.6×	122	2.7k

Countries citing papers authored by Jaewon Yang

Since Specialization

Citations

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

Fields of papers citing papers by Jaewon Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaewon Yang

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

All Works

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20 of 20 papers shown

Lee, Sangwon, et al.. (2025). Automated quantification of brain PET in PET/CT using deep learning-based CT-to-MR translation: a feasibility study. European Journal of Nuclear Medicine and Molecular Imaging. 52(8). 2959–2967.

Jang, Yongsun, et al.. (2024). Advanced pattern defect detection and analysis with artificial intelligence. 33. 47–47.

Caravaca, J., et al.. (2022). Comparison and calibration of dose delivered by ¹³⁷Cs and x-ray irradiators in mice. Physics in Medicine and Biology. 67(22). 225017–225017.

Sohn, Jae Ho, Yixin Chen, Dmytro Lituiev, et al.. (2022). Prediction of future healthcare expenses of patients from chest radiographs using deep learning: a pilot study. Scientific Reports. 12(1). 8344–8344. 4 indexed citations

Yang, Jaewon, Luyao Shi, Rui Wang, et al.. (2021). Direct image-based attenuation correction using conditional generative adversarial network for SPECT myocardial perfusion imaging. PubMed. 11600. 27–27. 15 indexed citations

Yang, Jaewon, Luyao Shi, Rui Wang, et al.. (2021). Direct Attenuation Correction Using Deep Learning for Cardiac SPECT: A Feasibility Study. Journal of Nuclear Medicine. 62(11). 1645–1652. 37 indexed citations

Gong, Kuang, Jaewon Yang, Peder E. Z. Larson, et al.. (2020). MR-Based Attenuation Correction for Brain PET Using 3-D Cycle-Consistent Adversarial Network. IEEE Transactions on Radiation and Plasma Medical Sciences. 5(2). 185–192. 29 indexed citations

Yang, Jaewon, Jae Ho Sohn, Spencer C. Behr, G.T. Gullberg, & Youngho Seo. (2020). CT-less Direct Correction of Attenuation and Scatter in the Image Space Using Deep Learning for Whole-Body FDG PET: Potential Benefits and Pitfalls. Radiology Artificial Intelligence. 3(2). e200137–e200137. 36 indexed citations

Gong, Kuang, Jiahui Guan, Kyungsang Kim, et al.. (2018). Iterative PET Image Reconstruction Using Convolutional Neural Network Representation. IEEE Transactions on Medical Imaging. 38(3). 675–685. 174 indexed citations

10.

Gong, Kuang, Jaewon Yang, Kyungsang Kim, et al.. (2018). Attenuation correction for brain PET imaging using deep neural network based on Dixon and ZTE MR images. Physics in Medicine and Biology. 63(12). 125011–125011. 84 indexed citations

11.

Leynes, Andrew P., Jaewon Yang, Florian Wiesinger, et al.. (2017). Zero-Echo-Time and Dixon Deep Pseudo-CT (ZeDD CT): Direct Generation of Pseudo-CT Images for Pelvic PET/MRI Attenuation Correction Using Deep Convolutional Neural Networks with Multiparametric MRI. Journal of Nuclear Medicine. 59(5). 852–858. 188 indexed citations

12.

Yang, Jaewon, Nathaniel W. Jenkins, Spencer C. Behr, et al.. (2017). Quantitative Evaluation of Atlas-based Attenuation Correction for Brain PET in an Integrated Time-of-Flight PET/MR Imaging System. Radiology. 284(1). 169–179. 18 indexed citations

13.

Yang, Jaewon, Florian Wiesinger, Sandeep Kaushik, et al.. (2017). Evaluation of Sinus/Edge-Corrected Zero-Echo-Time–Based Attenuation Correction in Brain PET/MRI. Journal of Nuclear Medicine. 58(11). 1873–1879. 33 indexed citations

14.

Yang, Jaewon, Tokihiro Yamamoto, Jonathan Berger, et al.. (2016). The impact of audiovisual biofeedback on 4D functional and anatomic imaging: Results of a lung cancer pilot study. Radiotherapy and Oncology. 120(2). 267–272. 8 indexed citations

15.

Choi, Joon Young, Jaewon Yang, Susan M. Noworolski, et al.. (2016). ¹⁸F Fluorocholine Dynamic Time-of-Flight PET/MR Imaging in Patients with Newly Diagnosed Intermediate- to High-Risk Prostate Cancer: Initial Clinical-Pathologic Comparisons. Radiology. 282(2). 429–436. 12 indexed citations

16.

Yang, Jaewon, Michel Tohme, Spencer C. Behr, et al.. (2015). Impact of atlas-CT-based bone anatomy compensation on MR-based attenuation correction for brain PET imaging in a time-of-flight PET/MRI system: A direct comparison to a patient-CT-based approach. EJNMMI Physics. 2(S1). A68–A68. 2 indexed citations

17.

Yang, Jaewon, Tokihiro Yamamoto, Samuel R. Mazin, Edward E. Graves, & Paul Keall. (2014). The potential of positron emission tomography for intratreatment dynamic lung tumor tracking: A phantom study. Medical Physics. 41(2). 21718–21718. 16 indexed citations

18.

Yang, Jaewon, Tokihiro Yamamoto, Billy W. Loo, et al.. (2013). Toward a planning scheme for emission guided radiation therapy (EGRT): FDG based tumor tracking in a metastatic breast cancer patient. Medical Physics. 40(8). 81708–81708. 20 indexed citations

19.

Yang, Jaewon, Tokihiro Yamamoto, Byungchul Cho, Youngho Seo, & Paul Keall. (2012). The impact of audio-visual biofeedback on 4D PET images: Results of a phantom study. Medical Physics. 39(2). 1046–1057. 18 indexed citations

20.

Yang, Jaewon, et al.. (2011). SU‐E‐J‐156: A Feasibility Study for Real‐Time Tumor Tracking Using Positron Emission Tomography (PET). Medical Physics. 38(6Part9). 3479–3479. 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.

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