Huiling Lu

995 total citations
43 papers, 682 citations indexed

About

Huiling Lu is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Huiling Lu has authored 43 papers receiving a total of 682 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 21 papers in Radiology, Nuclear Medicine and Imaging and 14 papers in Computer Vision and Pattern Recognition. Recurrent topics in Huiling Lu's work include AI in cancer detection (17 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and COVID-19 diagnosis using AI (12 papers). Huiling Lu is often cited by papers focused on AI in cancer detection (17 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and COVID-19 diagnosis using AI (12 papers). Huiling Lu collaborates with scholars based in China and United Kingdom. Huiling Lu's co-authors include Tao Zhou, Shi Qiu, Wenwen Wang, Yong Xia, Zaoli Yang, Yali Dong, Xinyu Ye, Hongbin Shi, Junjie Zhang and Hongwei Wang and has published in prestigious journals such as Scientific Reports, BioMed Research International and Applied Soft Computing.

In The Last Decade

Huiling Lu

35 papers receiving 660 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Huiling Lu China 9 291 272 151 59 58 43 682
Jumin Zhao China 15 328 1.1× 224 0.8× 120 0.8× 72 1.2× 64 1.1× 111 845
Dengao Li China 15 404 1.4× 272 1.0× 127 0.8× 66 1.1× 79 1.4× 91 807
Raul Victor M. da Nóbrega Brazil 9 249 0.9× 248 0.9× 184 1.2× 76 1.3× 70 1.2× 9 812
Ziming Wang China 9 332 1.1× 180 0.7× 184 1.2× 48 0.8× 53 0.9× 33 622
Ameer Hamza Pakistan 14 276 0.9× 236 0.9× 108 0.7× 63 1.1× 85 1.5× 46 617
Geraldo Bráz Brazil 16 332 1.1× 334 1.2× 321 2.1× 48 0.8× 46 0.8× 108 806
Ibrahem Kandel Portugal 9 204 0.7× 216 0.8× 201 1.3× 79 1.3× 34 0.6× 9 710
Alaa S. Al‐Waisy Iraq 16 250 0.9× 320 1.2× 261 1.7× 53 0.9× 29 0.5× 30 915
Belal Al‐Khateeb Iraq 15 396 1.4× 175 0.6× 119 0.8× 37 0.6× 57 1.0× 66 743
Tao Zhou China 14 365 1.3× 344 1.3× 274 1.8× 105 1.8× 80 1.4× 132 1.1k

Countries citing papers authored by Huiling Lu

Since Specialization
Citations

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

Fields of papers citing papers by Huiling Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Huiling Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Huiling Lu. A scholar is included among the top collaborators of Huiling 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 Huiling Lu. Huiling 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.
Zhang, Jingshen, Shuangxi Li, Huiling Lu, Liandong Zhu, & Fengchang Wu. (2025). Lighting strategy drives removal of ammonia nitrogen and phosphate in microalgae-bacteria consortia under tetracycline hydrochloride exposure. Algal Research. 88. 103989–103989. 1 indexed citations
2.
Zhou, Tao, et al.. (2025). Identity-Mapping ResFormer: A Computer-Aided Diagnosis Model for Pneumonia X-Ray Images. IEEE Transactions on Instrumentation and Measurement. 74. 1–12. 3 indexed citations
3.
Zhou, Tao, et al.. (2025). Model-data co-driven U-net segmentation network for multimodal lung tumor images. Applied Soft Computing. 180. 113410–113410.
4.
Zhou, Tao, et al.. (2024). Vision transformer: To discover the “four secrets” of image patches. Information Fusion. 105. 102248–102248. 17 indexed citations
5.
Zhou, Tao, Qianru Cheng, Xiangxiang Zhang, Qi Li, & Huiling Lu. (2024). PET/CT Cross-modal medical image fusion of lung tumors based on DCIF-GAN. Optics and Precision Engineering. 32(2). 221–236.
6.
Zhou, Tao, Qi Li, Huiling Lu, Long Liu, & Xiangxiang Zhang. (2024). UCP2-ACGAN: An adaptive condition GAN guided by U-shaped context perceptual processor for PET/CT images fusion. Biomedical Signal Processing and Control. 96. 106571–106571. 1 indexed citations
7.
Zhou, Tao, et al.. (2024). RNE-DSNet: A Re-parameterization Neighborhood Enhancement-based Dual-Stream Network for CT image recognition. Engineering Science and Technology an International Journal. 56. 101760–101760. 2 indexed citations
8.
Zhou, Tao, et al.. (2023). CCGL-YOLOV5:A cross-modal cross-scale global-local attention YOLOV5 lung tumor detection model. Computers in Biology and Medicine. 165. 107387–107387. 23 indexed citations
9.
Zhou, Tao, et al.. (2023). COVID-ResNet: COVID-19 Recognition Based on Improved Attention ResNet. Electronics. 12(6). 1413–1413. 5 indexed citations
10.
Zhou, Tao, et al.. (2022). Pooling Operations in Deep Learning: From “Invariable” to “Variable”. BioMed Research International. 2022(1). 4067581–4067581. 16 indexed citations
11.
Zhou, Tao, et al.. (2022). APU‐Net: An Attention Mechanism Parallel U‐Net for Lung Tumor Segmentation. BioMed Research International. 2022(1). 5303651–5303651. 8 indexed citations
12.
Zhou, Tao, Qi Li, Huiling Lu, Xiangxiang Zhang, & Qianru Cheng. (2022). Hybrid Multimodal Medical Image Fusion Method Based on LatLRR and ED-D2GAN. Applied Sciences. 12(24). 12758–12758. 5 indexed citations
13.
Zhou, Tao, et al.. (2022). Dense Convolutional Network and Its Application in Medical Image Analysis. BioMed Research International. 2022(1). 2384830–2384830. 116 indexed citations
14.
Zhou, Tao, et al.. (2021). A New Robust Adaptive Fusion Method for Double‐Modality Medical Image PET/CT. BioMed Research International. 2021(1). 3 indexed citations
15.
Zhou, Tao, et al.. (2021). 18F‐FDG‐PET/CT Whole‐Body Imaging Lung Tumor Diagnostic Model: An Ensemble E‐ResNet‐NRC with Divided Sample Space. BioMed Research International. 2021(1). 8865237–8865237. 5 indexed citations
16.
Zhou, Tao, et al.. (2020). Progress of residual neural network optimization algorithm for medical imaging disease diagnosis. Journal of Image and Graphics. 25(10). 2079–2092. 4 indexed citations
17.
Zhou, Tao, et al.. (2020). NSCR‐Based DenseNet for Lung Tumor Recognition Using Chest CT Image. BioMed Research International. 2020(1). 6636321–6636321. 12 indexed citations
18.
Zhou, Tao, Huiling Lu, Wenwen Wang, & Yong Xia. (2018). GA-SVM based feature selection and parameter optimization in hospitalization expense modeling. Applied Soft Computing. 75. 323–332. 182 indexed citations
19.
Zhou, Tao, Huiling Lu, Junjie Zhang, & Hongbin Shi. (2016). Pulmonary Nodule Detection Model Based on SVM and CT Image Feature-Level Fusion with Rough Sets. BioMed Research International. 2016. 1–13. 29 indexed citations
20.
Lu, Huiling. (2012). Clustering algorithm research advances on data mining. Computer Engineering and Applications Journal. 15 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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