Yushi Chang

424 total citations
21 papers, 316 citations indexed

About

Yushi Chang is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Radiation. According to data from OpenAlex, Yushi Chang has authored 21 papers receiving a total of 316 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Biomedical Engineering and 10 papers in Radiation. Recurrent topics in Yushi Chang's work include Medical Imaging Techniques and Applications (15 papers), Radiomics and Machine Learning in Medical Imaging (10 papers) and Advanced Radiotherapy Techniques (10 papers). Yushi Chang is often cited by papers focused on Medical Imaging Techniques and Applications (15 papers), Radiomics and Machine Learning in Medical Imaging (10 papers) and Advanced Radiotherapy Techniques (10 papers). Yushi Chang collaborates with scholars based in United States, China and Hong Kong. Yushi Chang's co-authors include F Yin, Chunhao Wang, Kyle J. Lafata, Lei Ren, Zhuoran Jiang, Yang Sheng, Jiahan Zhang, Yaorong Ge, Qiuwen Wu and John P. Kirkpatrick and has published in prestigious journals such as PLoS ONE, International Journal of Radiation Oncology*Biology*Physics and Physics in Medicine and Biology.

In The Last Decade

Yushi Chang

20 papers receiving 310 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yushi Chang United States 12 265 108 103 87 48 21 316
Xinzhi Teng Hong Kong 12 281 1.1× 78 0.7× 98 1.0× 76 0.9× 49 1.0× 41 356
Silvia Strolin Italy 9 218 0.8× 118 1.1× 129 1.3× 64 0.7× 31 0.6× 29 362
Jordan Wong Canada 8 204 0.8× 184 1.7× 93 0.9× 77 0.9× 47 1.0× 19 339
G. Guidi Italy 13 236 0.9× 138 1.3× 118 1.1× 63 0.7× 51 1.1× 35 388
Aditi Iyer United States 9 236 0.9× 71 0.7× 83 0.8× 58 0.7× 49 1.0× 16 291
Tanja Schimek‐Jasch Germany 16 261 1.0× 108 1.0× 189 1.8× 41 0.5× 24 0.5× 27 430
Kanabu Nawa Japan 9 385 1.5× 232 2.1× 170 1.7× 137 1.6× 58 1.2× 23 495
Ruijie Yang China 10 200 0.8× 206 1.9× 109 1.1× 101 1.2× 31 0.6× 26 364
Jinhan Zhu China 12 265 1.0× 244 2.3× 178 1.7× 82 0.9× 23 0.5× 43 449
Jaehee Chun South Korea 12 323 1.2× 230 2.1× 88 0.9× 100 1.1× 86 1.8× 28 438

Countries citing papers authored by Yushi Chang

Since Specialization
Citations

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

Fields of papers citing papers by Yushi Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yushi Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Yushi Chang. A scholar is included among the top collaborators of Yushi Chang 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 Yushi Chang. Yushi Chang 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.
Chang, Yushi, et al.. (2023). Cancer Control, Toxicity, and Secondary Malignancy Risks of Proton Radiation Therapy for Stage I-IIB Testicular Seminoma. Advances in Radiation Oncology. 8(5). 101259–101259. 6 indexed citations
2.
Huang, Mi, Zhuoran Jiang, Yushi Chang, et al.. (2022). Patient-specific deep learning model to enhance 4D-CBCT image for radiomics analysis. Physics in Medicine and Biology. 67(8). 85003–85003. 19 indexed citations
3.
Yang, Zhenyu, Kyle J. Lafata, Xinru Chen, et al.. (2022). Quantification of lung function on CT images based on pulmonary radiomic filtering. Medical Physics. 49(11). 7278–7286. 13 indexed citations
4.
Jiang, Zhuoran, et al.. (2022). Fast four‐dimensional cone‐beam computed tomography reconstruction using deformable convolutional networks. Medical Physics. 49(10). 6461–6476. 9 indexed citations
5.
Chang, Yushi, Zhuoran Jiang, W. Paul Segars, et al.. (2021). A generative adversarial network (GAN)-based technique for synthesizing realistic respiratory motion in the extended cardiac-torso (XCAT) phantoms. Physics in Medicine and Biology. 66(11). 115018–115018. 8 indexed citations
6.
Jiang, Zhuoran, et al.. (2021). Enhancement of 4-D Cone-Beam Computed Tomography (4D-CBCT) Using a Dual-Encoder Convolutional Neural Network (DeCNN). IEEE Transactions on Radiation and Plasma Medical Sciences. 6(2). 222–230. 13 indexed citations
7.
Lafata, Kyle J., Michael N. Corradetti, Junheng Gao, et al.. (2021). Radiogenomic Analysis of Locally Advanced Lung Cancer Based on CT Imaging and Intratreatment Changes in Cell-Free DNA. Radiology Imaging Cancer. 3(4). e200157–e200157. 35 indexed citations
8.
Jiang, Zhuoran, et al.. (2021). Real-Time Markerless Tracking of Lung Tumors Based on 2-D Fluoroscopy Imaging Using Convolutional LSTM. IEEE Transactions on Radiation and Plasma Medical Sciences. 6(2). 189–199. 5 indexed citations
9.
Lafata, Kyle J., Yushi Chang, Chunhao Wang, et al.. (2021). Intrinsic radiomic expression patterns after 20 Gy demonstrate early metabolic response of oropharyngeal cancers. Medical Physics. 48(7). 3767–3777. 19 indexed citations
10.
Jiang, Zhuoran, et al.. (2021). Prior image-guided cone-beam computed tomography augmentation from under-sampled projections using a convolutional neural network. Quantitative Imaging in Medicine and Surgery. 11(12). 4767–4780. 5 indexed citations
11.
Chang, Yushi, et al.. (2021). An AI-Enabled Virtual Hands-On Teaching Tool for Treatment Planning: A Pancreas SBRT Pilot Study. International Journal of Radiation Oncology*Biology*Physics. 111(3). e184–e184. 1 indexed citations
12.
Chang, Yushi, et al.. (2020). Digital phantoms for characterizing inconsistencies among radiomics extraction toolboxes. Biomedical Physics & Engineering Express. 6(2). 25016–25016. 20 indexed citations
13.
Wang, Chunhao, Chenyang Liu, Yushi Chang, et al.. (2020). Dose-Distribution-Driven PET Image-Based Outcome Prediction (DDD-PIOP): A Deep Learning Study for Oropharyngeal Cancer IMRT Application. Frontiers in Oncology. 10. 1592–1592. 23 indexed citations
14.
Huang, Mi, Zhuoran Jiang, Yushi Chang, et al.. (2020). 4D radiomics: impact of 4D-CBCT image quality on radiomic analysis. Physics in Medicine and Biology. 66(4). 45023–45023. 17 indexed citations
15.
Chang, Yushi, Kyle J. Lafata, W. Paul Segars, F Yin, & Lei Ren. (2020). Development of realistic multi-contrast textured XCAT (MT-XCAT) phantoms using a dual-discriminator conditional-generative adversarial network (D-CGAN). Physics in Medicine and Biology. 65(6). 65009–65009. 12 indexed citations
16.
Jiang, Zhuoran, et al.. (2020). Building a patient-specific model using transfer learning for four-dimensional cone beam computed tomography augmentation. Quantitative Imaging in Medicine and Surgery. 11(2). 540–555. 15 indexed citations
17.
Zhang, Jiahan, Yang Sheng, Yushi Chang, et al.. (2020). Automatic IMRT planning via static field fluence prediction (AIP-SFFP): a deep learning algorithm for real-time prostate treatment planning. Physics in Medicine and Biology. 65(17). 175014–175014. 53 indexed citations
18.
Chang, Yushi, Kyle J. Lafata, Wenzheng Sun, et al.. (2019). An investigation of machine learning methods in delta-radiomics feature analysis. PLoS ONE. 14(12). e0226348–e0226348. 41 indexed citations
19.
Wang, C., et al.. (2019). Rapid Auto IMRT Planning Using Cascade Dense Convolutional Neural Network (CDCNN): A Feasibility Study for Fluence Map Prediction Using Deep Learning on Prostate IMRT Patients. International Journal of Radiation Oncology*Biology*Physics. 105(1). E789–E790. 1 indexed citations
20.
Kim, David E., et al.. (2006). An Automatic Seeding System Using Machine Vision for Seed Line-up of Cucurbitaceous Vegetables. 2006 Portland, Oregon, July 9-12, 2006.

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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