Lida Qiu

500 total citations
27 papers, 327 citations indexed

About

Lida Qiu is a scholar working on Biophysics, Biomedical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Lida Qiu has authored 27 papers receiving a total of 327 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Biophysics, 9 papers in Biomedical Engineering and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Lida Qiu's work include Photoacoustic and Ultrasonic Imaging (9 papers), Advanced Fluorescence Microscopy Techniques (8 papers) and Cell Image Analysis Techniques (5 papers). Lida Qiu is often cited by papers focused on Photoacoustic and Ultrasonic Imaging (9 papers), Advanced Fluorescence Microscopy Techniques (8 papers) and Cell Image Analysis Techniques (5 papers). Lida Qiu collaborates with scholars based in China, United States and Singapore. Lida Qiu's co-authors include Qingxiang Wu, Jianxin Chen, Lianhuang Li, Deyong Kang, Wenhui Guo, Jiajia He, Gangqin Xi, Liqin Zheng, Haohua Tu and Fangmeng Fu and has published in prestigious journals such as Nature Communications, International Journal of Cancer and IEEE Access.

In The Last Decade

Lida Qiu

26 papers receiving 321 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lida Qiu China 10 97 89 75 67 56 27 327
Saad Ullah Akram Finland 8 50 0.5× 164 1.8× 59 0.8× 46 0.7× 48 0.9× 13 437
Anna Korzyńska Poland 12 32 0.3× 115 1.3× 129 1.7× 52 0.8× 81 1.4× 36 417
Tianyi Zhu China 11 72 0.7× 39 0.4× 56 0.7× 31 0.5× 8 0.1× 25 364
Wiebke Laffers Germany 11 109 1.1× 30 0.3× 175 2.3× 35 0.5× 106 1.9× 25 389
Ju Han United States 13 50 0.5× 220 2.5× 150 2.0× 83 1.2× 86 1.5× 23 482
Leslie Solorzano Sweden 7 35 0.4× 58 0.7× 114 1.5× 27 0.4× 122 2.2× 12 343
Kimmo Kartasalo Finland 14 98 1.0× 94 1.1× 126 1.7× 44 0.7× 147 2.6× 33 633
Maria Gabrani Switzerland 12 58 0.6× 164 1.8× 55 0.7× 53 0.8× 195 3.5× 39 469
Marco Wiltgen Austria 11 82 0.8× 30 0.3× 58 0.8× 125 1.9× 83 1.5× 30 407

Countries citing papers authored by Lida Qiu

Since Specialization
Citations

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

Fields of papers citing papers by Lida Qiu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lida Qiu

This figure shows the co-authorship network connecting the top 25 collaborators of Lida Qiu. A scholar is included among the top collaborators of Lida Qiu 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 Lida Qiu. Lida Qiu 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.
Liu, Yulan, Lianhuang Li, Liqin Zheng, et al.. (2024). Improving the diagnosis of ductal carcinoma in situ with microinvasion without immunohistochemistry: An innovative method with H&E‐stained and multiphoton microscopy images. International Journal of Cancer. 154(10). 1802–1813. 2 indexed citations
2.
Kang, Deyong, Chuan Wang, Fangmeng Fu, et al.. (2024). Exploration of the relationship between tumor-infiltrating lymphocyte score and histological grade in breast cancer. BMC Cancer. 24(1). 318–318. 1 indexed citations
3.
Huang, Xingxin, Fangmeng Fu, Deyong Kang, et al.. (2023). Prognostic significance of collagen signatures at breast tumor boundary obtained by combining multiphoton imaging and imaging analysis. Cellular Oncology. 47(1). 69–80. 3 indexed citations
4.
Xi, Gangqin, Chen Huang, Jie Lin, et al.. (2023). Rapid label‐free detection of early‐stage lung adenocarcinoma and tumor boundary via multiphoton microscopy. Journal of Biophotonics. 16(11). e202300172–e202300172. 3 indexed citations
5.
Huang, Xingxin, Lida Qiu, Xunbin Yu, et al.. (2023). Detection of fibrotic changes in the progression of liver diseases by label‐free multiphoton imaging. Journal of Biophotonics. 16(10). e202300153–e202300153. 3 indexed citations
6.
Huang, Xingxin, Lida Qiu, Xunbin Yu, et al.. (2023). Quantitative Assessment of Hepatic Steatosis Using Label-Free Multiphoton Imaging and Customized Image Processing Program. Laboratory Investigation. 103(10). 100223–100223.
7.
Chen, Jianhua, Zhijun Li, Deyong Kang, et al.. (2023). Prognostic value of tumor necrosis based on the evaluation of frequency in invasive breast cancer. BMC Cancer. 23(1). 530–530. 8 indexed citations
8.
Liu, Yulan, Deyong Kang, Xingxin Huang, et al.. (2022). Quantitative analysis of collagen morphology in breast cancer from millimeter scale using multiphoton microscopy. Journal of Innovative Optical Health Sciences. 16(4). 1 indexed citations
9.
Qiu, Lida, Deyong Kang, Wenhui Guo, et al.. (2022). Intratumor graph neural network recovers hidden prognostic value of multi-biomarker spatial heterogeneity. Nature Communications. 13(1). 4250–4250. 18 indexed citations
10.
Liu, Tianjian, et al.. (2022). An antagonistic training algorithm for TFT-LCD module mura defect detection. Signal Processing Image Communication. 107. 116791–116791. 14 indexed citations
11.
He, Jiajia, Deyong Kang, Liqin Zheng, et al.. (2022). Label‐free detection of invasive micropapillary carcinoma of the breast using multiphoton microscopy. Journal of Biophotonics. 16(3). e202200224–e202200224. 4 indexed citations
12.
Liu, Tianjian, et al.. (2022). Enhanced ResNet-based super-resolution method for two-photon microscopy image. Signal Image and Video Processing. 16(8). 2157–2163. 1 indexed citations
13.
Xi, Gangqin, Lida Qiu, Shuoyu Xu, et al.. (2021). Computer-assisted quantification of tumor-associated collagen signatures to improve the prognosis prediction of breast cancer. BMC Medicine. 19(1). 273–273. 33 indexed citations
14.
He, Jiajia, Fangmeng Fu, Wei Wang, et al.. (2021). Prognostic value of tumour-infiltrating lymphocytes based on the evaluation of frequency in patients with oestrogen receptor–positive breast cancer. European Journal of Cancer. 154. 217–226. 11 indexed citations
15.
Xi, Gangqin, Wenhui Guo, Deyong Kang, et al.. (2021). Large-scale tumor-associated collagen signatures identify high-risk breast cancer patients. Theranostics. 11(7). 3229–3243. 78 indexed citations
16.
Li, Lianhuang, Shenghui Huang, Lida Qiu, et al.. (2020). Label-Free Identification of Early Gastrointestinal Neuroendocrine Tumors via Biomedical Multiphoton Microscopy and Automatic Image Analysis. IEEE Access. 8. 105681–105689. 3 indexed citations
17.
Li, Lianhuang, et al.. (2020). Label-free multiphoton imaging to assess neoadjuvant therapy responses in breast carcinoma. International Journal of Biological Sciences. 16(8). 1376–1387. 11 indexed citations
18.
Wu, Qingxiang, et al.. (2017). Image super-resolution using a dilated convolutional neural network. Neurocomputing. 275. 1219–1230. 77 indexed citations
19.
Qiu, Lida, Ping Fu, & Tianjian Liu. (2015). Research on Image Segmentation Algorithm Based on Entropy and PSO Algorithm. The Open Automation and Control Systems Journal. 7(1). 1301–1306. 3 indexed citations
20.

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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