Zixiao Lu

879 total citations
20 papers, 602 citations indexed

About

Zixiao Lu is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Rheumatology. According to data from OpenAlex, Zixiao Lu has authored 20 papers receiving a total of 602 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Artificial Intelligence and 5 papers in Rheumatology. Recurrent topics in Zixiao Lu's work include Radiomics and Machine Learning in Medical Imaging (9 papers), AI in cancer detection (8 papers) and Cancer Genomics and Diagnostics (4 papers). Zixiao Lu is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (9 papers), AI in cancer detection (8 papers) and Cancer Genomics and Diagnostics (4 papers). Zixiao Lu collaborates with scholars based in China, United States and Hong Kong. Zixiao Lu's co-authors include Wei Shao, Kun Huang, Jie Zhang, Qianjin Feng, Tongxin Wang, Zhi Han, Wei Yang, Bryan R. Helm, Travis S. Johnson and Chunyan Deng and has published in prestigious journals such as Genome biology, IEEE Transactions on Medical Imaging and Medical Image Analysis.

In The Last Decade

Zixiao Lu

20 papers receiving 594 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zixiao Lu China 10 380 265 142 107 70 20 602
Anurag Vaidya United States 8 407 1.1× 480 1.8× 130 0.9× 107 1.0× 104 1.5× 10 865
Maha Shady United States 5 270 0.7× 354 1.3× 97 0.7× 98 0.9× 70 1.0× 10 522
Mane Williams United States 5 338 0.9× 431 1.6× 127 0.9× 114 1.1× 107 1.5× 6 707
Charlie Saillard France 6 433 1.1× 379 1.4× 116 0.8× 145 1.4× 146 2.1× 12 754
Eirini Arvaniti Switzerland 6 163 0.4× 246 0.9× 148 1.0× 44 0.4× 73 1.0× 9 558
Meriem Sefta France 5 305 0.8× 347 1.3× 143 1.0× 155 1.4× 157 2.2× 6 688
Andrew Zhang United States 4 265 0.7× 362 1.4× 88 0.6× 58 0.5× 84 1.2× 6 619
Amelie Echle Germany 9 350 0.9× 362 1.4× 84 0.6× 115 1.1× 198 2.8× 10 618
Guillaume Jaume United States 11 401 1.1× 577 2.2× 124 0.9× 85 0.8× 114 1.6× 14 885
Nathan Ing United States 6 165 0.4× 217 0.8× 107 0.8× 57 0.5× 80 1.1× 11 411

Countries citing papers authored by Zixiao Lu

Since Specialization
Citations

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

Fields of papers citing papers by Zixiao Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zixiao Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Zixiao Lu. A scholar is included among the top collaborators of Zixiao Lu 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 Zixiao Lu. Zixiao Lu 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.
Lu, Zixiao, Menghong Wang, Xinai Han, et al.. (2024). Artificial intelligence improves the diagnosis of human leukocyte antigen (HLA)-B27-negative axial spondyloarthritis based on multi-sequence magnetic resonance imaging and clinical features. Quantitative Imaging in Medicine and Surgery. 14(8). 5845–5860. 1 indexed citations
2.
Lu, Zixiao, Kai Tang, Yi Wu, et al.. (2024). BreasTDLUSeg: A coarse-to-fine framework for segmentation of breast terminal duct lobular units on histopathological whole-slide images. Computerized Medical Imaging and Graphics. 118. 102432–102432. 2 indexed citations
3.
4.
Li, Xin, Yi Lin, Zixiao Lu, et al.. (2024). Automatic segmentation of fat metaplasia on sacroiliac joint MRI using deep learning. Insights into Imaging. 15(1). 93–93. 2 indexed citations
5.
Shao, Wei, Yangyang Shi, Yawen Wu, et al.. (2023). Characterizing the Survival-Associated Interactions Between Tumor-Infiltrating Lymphocytes and Tumors From Pathological Images and Multi-Omics Data. IEEE Transactions on Medical Imaging. 42(10). 3025–3035. 9 indexed citations
6.
7.
Tang, Kai, et al.. (2022). DDTNet: A dense dual-task network for tumor-infiltrating lymphocyte detection and segmentation in histopathological images of breast cancer. Medical Image Analysis. 78. 102415–102415. 44 indexed citations
8.
9.
Lu, Zixiao, Xiaohui Zhan, Yi Wu, et al.. (2021). BrcaSeg : A Deep Learning Approach for Tissue Quantification and Genomic Correlations of Histopathological Images. Genomics Proteomics & Bioinformatics. 19(6). 1032–1042. 11 indexed citations
10.
Lu, Zixiao, Hao Chen, Qiang Ye, et al.. (2021). Prediction of Treatment Response According to ASAS-EULAR Management Recommendations in 1 Year for Hip Involvement in Axial Spondyloarthritis Based on MRI and Clinical Indicators. Frontiers in Endocrinology. 12. 771997–771997. 1 indexed citations
11.
Lu, Zixiao, Wei Shao, Yi Wu, et al.. (2020). Deep-Learning–Based Characterization of Tumor-Infiltrating Lymphocytes in Breast Cancers From Histopathology Images and Multiomics Data. JCO Clinical Cancer Informatics. 4(4). 480–490. 65 indexed citations
12.
Lu, Zixiao, Wei Shao, Christina Y. Yu, et al.. (2020). Integrative analysis of histopathological images and chromatin accessibility data for estrogen receptor-positive breast cancer. BMC Medical Genomics. 13(S11). 195–195. 7 indexed citations
13.
Feng, Weixing, Zixiao Lu, Christina Y. Yu, et al.. (2020). regSNPs-ASB: A Computational Framework for Identifying Allele-Specific Transcription Factor Binding From ATAC-seq Data. Frontiers in Bioengineering and Biotechnology. 8. 886–886. 7 indexed citations
14.
15.
Zhao, Lijun, Zixiao Lu, Jun Jiang, et al.. (2019). Automatic Nasopharyngeal Carcinoma Segmentation Using Fully Convolutional Networks with Auxiliary Paths on Dual-Modality PET-CT Images. Journal of Digital Imaging. 32(3). 462–470. 51 indexed citations
16.
Wang, Tongxin, Travis S. Johnson, Wei Shao, et al.. (2019). BERMUDA: a novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes. Genome biology. 20(1). 165–165. 95 indexed citations
17.
Shao, Wei, Kun Huang, Zhi Han, et al.. (2019). Integrative Analysis of Pathological Images and Multi-Dimensional Genomic Data for Early-Stage Cancer Prognosis. IEEE Transactions on Medical Imaging. 39(1). 99–110. 77 indexed citations
18.
Dong, Yuhao, Qianjin Feng, Wei Yang, et al.. (2017). Preoperative prediction of sentinel lymph node metastasis in breast cancer based on radiomics of T2-weighted fat-suppression and diffusion-weighted MRI. European Radiology. 28(2). 582–591. 197 indexed citations
19.
Ji, Lei, et al.. (2017). [Application study of qualitatively diagnosing prostate cancer using ultrahigh b-value DWI].. PubMed. 97(27). 2107–2110. 1 indexed citations
20.
Zhong, Liming, Liyan Lin, Zhentai Lu, et al.. (2016). Predict CT image from MRI data using KNN-regression with learned local descriptors. 743–746. 13 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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