Steve Jiang

906 total citations
25 papers, 678 citations indexed

About

Steve Jiang is a scholar working on Radiation, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Steve Jiang has authored 25 papers receiving a total of 678 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Radiation, 14 papers in Radiology, Nuclear Medicine and Imaging and 13 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Steve Jiang's work include Advanced Radiotherapy Techniques (15 papers), Radiomics and Machine Learning in Medical Imaging (8 papers) and Medical Imaging Techniques and Applications (6 papers). Steve Jiang is often cited by papers focused on Advanced Radiotherapy Techniques (15 papers), Radiomics and Machine Learning in Medical Imaging (8 papers) and Medical Imaging Techniques and Applications (6 papers). Steve Jiang collaborates with scholars based in United States and China. Steve Jiang's co-authors include Jun Deng, Todd Pawlicki, Jinsheng Li, Tong Lin, Xiaoli Tang, Ajay Kapur, Kevin Albuquerque, Laura Cerviño, Zichun Zhong and Xuejun Gu and has published in prestigious journals such as International Journal of Radiation Oncology*Biology*Physics, IEEE Access and Physics in Medicine and Biology.

In The Last Decade

Steve Jiang

21 papers receiving 663 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Steve Jiang United States 9 493 413 378 185 63 25 678
Wouter Crijns Belgium 18 850 1.7× 662 1.6× 559 1.5× 218 1.2× 68 1.1× 59 1.1k
Gerd Heilemann Austria 12 367 0.7× 298 0.7× 252 0.7× 92 0.5× 37 0.6× 31 501
John A. Mills United Kingdom 14 458 0.9× 368 0.9× 302 0.8× 106 0.6× 52 0.8× 40 595
R Siochi United States 14 521 1.1× 428 1.0× 341 0.9× 172 0.9× 21 0.3× 51 681
Jong Hwi Jeong South Korea 13 481 1.0× 457 1.1× 377 1.0× 157 0.8× 42 0.7× 68 722
Giovanni Borasi Italy 15 182 0.4× 371 0.9× 382 1.0× 271 1.5× 76 1.2× 50 646
Peter Kuess Austria 17 568 1.2× 333 0.8× 588 1.6× 98 0.5× 42 0.7× 57 844
Andrea McNiven Canada 11 564 1.1× 496 1.2× 380 1.0× 169 0.9× 44 0.7× 42 767
Jianrong Dai China 11 443 0.9× 483 1.2× 241 0.6× 171 0.9× 53 0.8× 44 616
Xingen Wu United States 14 445 0.9× 314 0.8× 333 0.9× 86 0.5× 19 0.3× 29 612

Countries citing papers authored by Steve Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Steve Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Steve Jiang

This figure shows the co-authorship network connecting the top 25 collaborators of Steve Jiang. A scholar is included among the top collaborators of Steve Jiang 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 Steve Jiang. Steve Jiang 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.
2.
Shen, Chenyang, T. Banks, Hao Peng, et al.. (2025). Expanding SCINTIX Biology-Guided Radiotherapy Beyond Lung and Bone: A Planning Feasibility and Dosimetric Study on the RefleXion X1 System. Technology in Cancer Research & Treatment. 24. 2244107222–2244107222.
3.
Dohopolski, Michael, et al.. (2025). Deep unsupervised clustering for prostate auto-segmentation with and without hydrogel spacer. Machine Learning Science and Technology. 6(1). 15015–15015. 1 indexed citations
4.
Jiang, Steve, et al.. (2025). Medical image segmentation assisted with clinical inputs via language encoder in a deep learning framework. Machine Learning Science and Technology. 6(1). 15040–15040.
5.
6.
Liang, Xiao, Howard E. Morgan, Ti Bai, et al.. (2023). Deep learning based direct segmentation assisted by deformable image registration for cone-beam CT based auto-segmentation for adaptive radiotherapy. Physics in Medicine and Biology. 68(4). 45012–45012. 7 indexed citations
7.
Li, Shulong, Bin Li, Liyuan Chen, et al.. (2019). Predicting lung nodule malignancies by combining deep convolutional neural network and handcrafted features. Physics in Medicine and Biology. 64(17). 175012–175012. 61 indexed citations
8.
Lin, Mu‐Han, et al.. (2018). Convolution‐based modified Clarkson integration (CMCI) for electron cutout factor calculation. Journal of Applied Clinical Medical Physics. 19(2). 128–136. 1 indexed citations
9.
Zhen, Xin, Zichun Zhong, Brian Hrycushko, et al.. (2017). Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study. Physics in Medicine and Biology. 62(21). 8246–8263. 134 indexed citations
10.
Chiu, Tsuicheng, Jun Tan, Tammy M. Long, et al.. (2017). 3D printer-assisted Soft Silicone Compensators for Electron Modulated Radiotherapy. International Journal of Radiation Oncology*Biology*Physics. 99(2). E649–E649. 2 indexed citations
11.
Long, Troy, et al.. (2016). Continuous leaf optimization for IMRT leaf sequencing. Medical Physics. 43(10). 5403–5411. 6 indexed citations
12.
Jiang, Steve, et al.. (2015). VMATc: VMAT with constant gantry speed and dose rate. Physics in Medicine and Biology. 60(7). 2955–2979. 9 indexed citations
13.
Huang, Wei, Xun Jia, Bin Dong, et al.. (2011). TU-C-214-03: Markerless Tumor Tracking via Clustering on Low-Rank Fluoroscopic Images for Image-Guided Lung Cancer Radiotherapy. Medical Physics. 38(6Part28). 3756–3756.
14.
Lin, Tong, Ruijiang Li, Xiaoli Tang, Jennifer Dy, & Steve Jiang. (2009). Markerless gating for lung cancer radiotherapy based on machine learning techniques. Physics in Medicine and Biology. 54(6). 1555–1563. 34 indexed citations
15.
Lin, Tong, Laura Cerviño, Xiaoli Tang, Nuno Vasconcelos, & Steve Jiang. (2009). Fluoroscopic tumor tracking for image-guided lung cancer radiotherapy. Physics in Medicine and Biology. 54(4). 981–992. 83 indexed citations
16.
Cui, Ying, Jennifer Dy, Brian M. Alexander, & Steve Jiang. (2008). Fluoroscopic gating without implanted fiducial markers for lung cancer radiotherapy based on support vector machines. Physics in Medicine and Biology. 53(16). N315–N327. 35 indexed citations
17.
Deng, Jun, et al.. (2001). Derivation of electron and photon energy spectra from electron beam central axis depth dose curves. Physics in Medicine and Biology. 46(5). 1429–1449. 38 indexed citations
18.
Deng, Jun, et al.. (2000). Photon beam characterization and modelling for Monte Carlo treatment planning. Physics in Medicine and Biology. 45(2). 411–427. 116 indexed citations
19.
Jiang, Steve, et al.. (1999). Monte Carlo modelling of electron beams from medical accelerators. Physics in Medicine and Biology. 44(12). R157–R189. 133 indexed citations
20.
Jiang, Steve, Zhengming Luo, Todd Pawlicki, & Komanduri M. Ayyangar. (1997). A fast numerical algorithm for electron mean energy calculation in radiation therapy. Computers in Biology and Medicine. 27(6). 487–491. 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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