Junshen Xu

1.1k total citations
13 papers, 360 citations indexed

About

Junshen Xu is a scholar working on Pediatrics, Perinatology and Child Health, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Junshen Xu has authored 13 papers receiving a total of 360 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Pediatrics, Perinatology and Child Health, 6 papers in Artificial Intelligence and 6 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Junshen Xu's work include Fetal and Pediatric Neurological Disorders (7 papers), Domain Adaptation and Few-Shot Learning (6 papers) and Neonatal and fetal brain pathology (5 papers). Junshen Xu is often cited by papers focused on Fetal and Pediatric Neurological Disorders (7 papers), Domain Adaptation and Few-Shot Learning (6 papers) and Neonatal and fetal brain pathology (5 papers). Junshen Xu collaborates with scholars based in United States, China and United Kingdom. Junshen Xu's co-authors include Enhao Gong, John M. Pauly, Elfar Adalsteinsson, Polina Golland, Greg Zaharchuk, Kevin T. Chen, Michael D. Greicius, Fabíola Macruz, Athanasia Boumis and P. Ellen Grant and has published in prestigious journals such as Stroke, Radiology and Magnetic Resonance in Medicine.

In The Last Decade

Junshen Xu

13 papers receiving 357 citations

Peers

Junshen Xu

RNMI

PPCH

CVPR

Lucas Fidon United Kingdom

Joshua V. Stough United States

Gillian Macnaught United Kingdom

Jens Sjölund Sweden

Sahar Ahmad United States

Hessam Sokooti Netherlands

Ying‐Hwey Nai Singapore

Mahmut Yurt United States

Muzaffer Özbey Türkiye

Yannick Suter Switzerland

Lucas Fidon United Kingdom

Junshen Xu

216 ×0.8

RNMI

84 ×1.1

37 ×0.5

PPCH

131 ×1.9

138 ×2.2

CVPR

Citations per year, relative to Junshen Xu Junshen Xu (= 1×) peers Lucas Fidon

Countries citing papers authored by Junshen Xu

Since Specialization

Citations

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

Fields of papers citing papers by Junshen Xu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junshen Xu

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

All Works

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13 of 13 papers shown

Xu, Junshen, Zijing Dong, Fuyixue Wang, et al.. (2023). Latent signal models: Learning compact representations of signal evolution for improved time‐resolved, multi‐contrast MRI. Magnetic Resonance in Medicine. 90(2). 483–501. 4 indexed citations

Xu, Junshen, Daniel Moyer, Borjan Gagoski, et al.. (2023). NeSVoR: Implicit Neural Representation for Slice-to-Volume Reconstruction in MRI. IEEE Transactions on Medical Imaging. 42(6). 1707–1719. 37 indexed citations

Xu, Junshen, et al.. (2022). SVoRT: Iterative Transformer for Slice-to-Volume Registration in Fetal Brain MRI. Lecture notes in computer science. 13436. 3–13. 16 indexed citations

Vasung, Lana, Junshen Xu, Elizabeth A. Holland, et al.. (2022). Cross-Sectional Observational Study of Typical in utero Fetal Movements Using Machine Learning. Developmental Neuroscience. 45(3). 105–114. 3 indexed citations

Gagoski, Borjan, Junshen Xu, Paul Wighton, et al.. (2021). Automated detection and reacquisition of motion‐degraded images in fetal HASTE imaging at 3 T. Magnetic Resonance in Medicine. 87(4). 1914–1922. 20 indexed citations

Xu, Junshen, Esra Abacı Türk, P. Ellen Grant, Polina Golland, & Elfar Adalsteinsson. (2021). STRESS: Super-Resolution for Dynamic Fetal MRI Using Self-supervised Learning. Lecture notes in computer science. 12907. 197–206. 7 indexed citations

Xu, Junshen, Borjan Gagoski, Esra Abacı Türk, et al.. (2020). Semi-supervised Learning for Fetal Brain MRI Quality Assessment with ROI Consistency. Lecture notes in computer science. 12266. 386–395. 11 indexed citations

Xu, Junshen, et al.. (2020). Enhanced Detection of Fetal Pose in 3D MRI by Deep Reinforcement Learning with Physical Structure Priors on Anatomy. Lecture notes in computer science. 12266. 396–405. 6 indexed citations

Xu, Junshen, et al.. (2020). Ultra-low-dose 18F-FDG brain PET/MR denoising using deep learning and multi-contrast information. 60–60. 17 indexed citations

10.

Jiang, Mengmeng, Yiqian Zhang, Junshen Xu, et al.. (2019). Assessing EGFR gene mutation status in non-small cell lung cancer with imaging features from PET/CT. Nuclear Medicine Communications. 40(8). 842–849. 33 indexed citations

11.

Xu, Junshen, Esra Abacı Türk, Larry Zhang, et al.. (2019). Fetal Pose Estimation in Volumetric MRI Using a 3D Convolution Neural Network. Lecture notes in computer science. 11767. 403–410. 22 indexed citations

12.

Chen, Kevin T., Enhao Gong, Fabíola Macruz, et al.. (2018). Ultra–Low-Dose¹⁸F-Florbetaben Amyloid PET Imaging Using Deep Learning with Multi-Contrast MRI Inputs. Radiology. 290(3). 649–656. 182 indexed citations

13.

Niu, Yilin, Enhao Gong, Junshen Xu, John M. Pauly, & Greg Zaharchuk. (2018). Abstract WP53: Improved Prediction of the Final Infarct From Acute Stroke Neuroimaging Using Deep Learning. Stroke. 49(Suppl_1). 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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