Song Xue

416 total citations
31 papers, 250 citations indexed

About

Song Xue is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Radiation. According to data from OpenAlex, Song Xue has authored 31 papers receiving a total of 250 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Biomedical Engineering and 6 papers in Radiation. Recurrent topics in Song Xue's work include Medical Imaging Techniques and Applications (21 papers), Radiomics and Machine Learning in Medical Imaging (14 papers) and Advanced X-ray and CT Imaging (13 papers). Song Xue is often cited by papers focused on Medical Imaging Techniques and Applications (21 papers), Radiomics and Machine Learning in Medical Imaging (14 papers) and Advanced X-ray and CT Imaging (13 papers). Song Xue collaborates with scholars based in Switzerland, China and Germany. Song Xue's co-authors include Kuangyu Shi, Axel Rominger, Hasan Sari, Marco Viscione, Biao Li, Rui Guo, Raphael Sznitman, Clemens Mingels, Ian Alberts and Xiaoyue Duan and has published in prestigious journals such as Nature Communications, Sensors and Neurocomputing.

In The Last Decade

Song Xue

26 papers receiving 248 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Song Xue Switzerland 9 185 58 57 26 21 31 250
Hiba Omer Saudi Arabia 9 153 0.8× 37 0.6× 87 1.5× 15 0.6× 11 0.5× 47 261
Mika Pollari Finland 8 110 0.6× 24 0.4× 102 1.8× 55 2.1× 30 1.4× 19 236
Leixin Zhou United States 5 198 1.1× 16 0.3× 77 1.4× 47 1.8× 34 1.6× 9 249
Tong Shan United States 7 269 1.5× 95 1.6× 100 1.8× 44 1.7× 22 1.0× 24 372
Hassan Mohy‐ud‐Din United States 9 157 0.8× 31 0.5× 49 0.9× 31 1.2× 19 0.9× 29 230
Vivek Walimbe United States 10 190 1.0× 40 0.7× 74 1.3× 132 5.1× 7 0.3× 18 320
Sorina Camarasu-Pop France 6 88 0.5× 31 0.5× 34 0.6× 40 1.5× 21 1.0× 15 219
Jianan Cui China 7 263 1.4× 61 1.1× 98 1.7× 81 3.1× 21 1.0× 24 316

Countries citing papers authored by Song Xue

Since Specialization
Citations

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

Fields of papers citing papers by Song Xue

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Song Xue

This figure shows the co-authorship network connecting the top 25 collaborators of Song Xue. A scholar is included among the top collaborators of Song Xue 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 Song Xue. Song Xue 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.
Xue, Song, Xinyu Zhang, Ying Miao, et al.. (2025). Clinical evaluation of deep learning-based CT-free PET reconstruction image: a dual-center study. European Journal of Nuclear Medicine and Molecular Imaging. 53(4). 2592–2603.
2.
Li, Xiaoxu, Song Xue, Jiyang Xie, et al.. (2025). Interactive triplet attention for few-shot fine-grained image classification. Neurocomputing. 655. 131377–131377.
3.
Rauscher, Isabel, Song Xue, Andrei Gafita, et al.. (2025). Characterization of Effective Half-Life for Instant Single-Time-Point Dosimetry Using Machine Learning. Journal of Nuclear Medicine. 66(5). 778–784. 3 indexed citations
4.
Xue, Song, Andrei Gafita, Thomas Wendler, et al.. (2024). PBPK-Adapted Deep Learning for Pretherapy Prediction of Voxelwise Dosimetry: In-Silico Proof of Concept. IEEE Transactions on Radiation and Plasma Medical Sciences. 8(6). 646–654. 5 indexed citations
5.
6.
Zhou, Xiang, Yu Fu, Lianghua Li, et al.. (2024). Intelligent ultrafast total-body PET for sedation-free pediatric [18F]FDG imaging. European Journal of Nuclear Medicine and Molecular Imaging. 51(8). 2353–2366. 8 indexed citations
7.
8.
Zhang, Jing, Alexandre Bousse, Yanbin Li, et al.. (2024). Pre-therapy dose prediction in targeted radionuclide therapy using semi-supervised learning: An in-silico preliminary study. SPIRE - Sciences Po Institutional REpository. 1–1. 1 indexed citations
9.
Xue, Song, et al.. (2023). A deep learning method for the recovery of standard-dose imaging quality from ultra-low-dose PET on wavelet domain. Nuklearmedizin - NuclearMedicine. 62(2). 166–167. 2 indexed citations
10.
Duan, Jin, et al.. (2023). Enhanced Pelican Optimization Algorithm for Cluster Head Selection in Heterogeneous Wireless Sensor Networks. Sensors. 23(18). 7711–7711. 16 indexed citations
11.
Guo, Rui, Ying Miao, Song Xue, et al.. (2023). Cross-Scanner Low-Dose Brain-PET Image Noise Reduction With Self-Ensembling. IEEE Transactions on Radiation and Plasma Medical Sciences. 8(4). 391–401. 2 indexed citations
12.
Vandenberghe, Stefaan, Nadia Withofs, M. Dadgar, et al.. (2023). Walk-through flat panel total-body PET: a patient-centered design for high throughput imaging at lower cost using DOI-capable high-resolution monolithic detectors. European Journal of Nuclear Medicine and Molecular Imaging. 50(12). 3558–3571. 16 indexed citations
13.
Hu, Jiaxi, Stavroula Mougiakakou, Song Xue, et al.. (2023). Artificial intelligence for reducing the radiation burden of medical imaging for the diagnosis of coronavirus disease. The European Physical Journal Plus. 138(5). 1 indexed citations
14.
Guo, Rui, Song Xue, Jiaxi Hu, et al.. (2022). Using domain knowledge for robust and generalizable deep learning-based CT-free PET attenuation and scatter correction. Nature Communications. 13(1). 5882–5882. 36 indexed citations
15.
Sari, Hasan, Clemens Mingels, Ian Alberts, et al.. (2022). Quantitative evaluation of a deep learning-based framework to generate whole-body attenuation maps using LSO background radiation in long axial FOV PET scanners. European Journal of Nuclear Medicine and Molecular Imaging. 49(13). 4490–4502. 20 indexed citations
16.
Hu, Jiaxi, Hasan Sari, Song Xue, et al.. (2022). An encoder-decoder network for direct image reconstruction on sinograms of a long axial field of view PET. European Journal of Nuclear Medicine and Molecular Imaging. 49(13). 4464–4477. 17 indexed citations
17.
Li, Y, Jicun Hu, Hasan Sari, et al.. (2022). A deep neural network for parametric image reconstruction on a large axial field-of-view PET. European Journal of Nuclear Medicine and Molecular Imaging. 50(3). 701–714. 20 indexed citations
18.
Xue, Song, Rui Guo, Karl Peter Bohn, et al.. (2021). A cross-scanner and cross-tracer deep learning method for the recovery of standard-dose imaging quality from low-dose PET. European Journal of Nuclear Medicine and Molecular Imaging. 49(6). 1843–1856. 50 indexed citations
19.
Xue, Song, Xinsheng Jiang, & Jimiao Duan. (2017). A new box-counting method for image fractal dimension estimation. 28. 1786–1791. 3 indexed citations
20.
Lu, Wenjun, et al.. (2013). Remote sensing image quality assessment based on fractal theory. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8878. 88780Z–88780Z. 3 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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