Dong Ni

11.9k total citations · 3 hit papers
232 papers, 6.8k citations indexed

About

Dong Ni is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Dong Ni has authored 232 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Artificial Intelligence, 68 papers in Computer Vision and Pattern Recognition and 60 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Dong Ni's work include AI in cancer detection (44 papers), Radiomics and Machine Learning in Medical Imaging (31 papers) and Domain Adaptation and Few-Shot Learning (30 papers). Dong Ni is often cited by papers focused on AI in cancer detection (44 papers), Radiomics and Machine Learning in Medical Imaging (31 papers) and Domain Adaptation and Few-Shot Learning (30 papers). Dong Ni collaborates with scholars based in China, Hong Kong and United States. Dong Ni's co-authors include Tianfu Wang, Baiying Lei, Siping Chen, Jing Qin, Xin Yang, Shengli Li, Pheng‐Ann Heng, Yi Wang, Jie‐Zhi Cheng and Dinggang Shen and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Dong Ni

216 papers receiving 6.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

2016 529 citations Dong Ni, Jing Qin et al. profile →
Deep Learning in Medical Ultrasound Analysis: A Review

2019 521 citations Shengfeng Liu, Yi Wang et al. Engineering profile →
Segment anything model for medical images?

2023 215 citations Yuhao Huang, Xin Yang et al. Medical Image Analysis profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dong Ni China	43	2.5k	2.2k	1.8k	863	854	232	6.8k
Baiying Lei China	48	3.1k 1.3×	2.4k 1.1×	2.6k 1.4×	336 0.4×	741 0.9×	296	8.1k
Bradley J. Erickson United States	49	1.8k 0.7×	4.5k 2.1×	1.4k 0.7×	878 1.0×	1.4k 1.6×	280	10.4k
Georg Langs Austria	36	1.8k 0.7×	4.5k 2.0×	1.1k 0.6×	352 0.4×	1.1k 1.2×	226	9.6k
Yuanyuan Wang China	42	1.2k 0.5×	3.3k 1.5×	1.1k 0.6×	708 0.8×	1.9k 2.2×	533	8.2k
Ghassan Hamarneh Canada	39	1.8k 0.7×	1.9k 0.9×	2.7k 1.5×	321 0.4×	1.1k 1.2×	252	6.7k
Michael Fulham Australia	48	1.8k 0.7×	3.7k 1.7×	1.7k 0.9×	1.1k 1.2×	763 0.9×	269	9.0k
Siping Chen China	37	1.5k 0.6×	1.1k 0.5×	1.1k 0.6×	478 0.6×	1.4k 1.6×	271	4.9k
Guorong Wu United States	34	1.7k 0.7×	2.9k 1.3×	2.5k 1.3×	315 0.4×	851 1.0×	204	7.0k
Heung‐Il Suk South Korea	35	2.7k 1.1×	2.6k 1.2×	2.0k 1.1×	427 0.5×	947 1.1×	136	8.4k
Chandan Chakraborty India	46	1.2k 0.5×	736 0.3×	1.1k 0.6×	1.6k 1.8×	535 0.6×	178	7.2k

Countries citing papers authored by Dong Ni

Since Specialization

Citations

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

Fields of papers citing papers by Dong Ni

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dong Ni

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Guo, Ying, Yuhan Cai, Tao Xu, et al.. (2025). Echocardiographic video-driven multi-task learning model for coronary artery disease diagnosis and severity grading. Frontiers in Bioengineering and Biotechnology. 13. 1556748–1556748.

Huang, Yuhao, Allan Chang, Haoran Dou, et al.. (2025). Flip Learning: Weakly supervised erase to segment nodules in breast ultrasound. Medical Image Analysis. 102. 103552–103552. 1 indexed citations

Ni, Dong, et al.. (2025). ModeTv2: GPU-accelerated motion decomposition transformer for pairwise optimization in medical image registration. Medical Image Analysis. 108. 103862–103862.

Zhang, Zhiguo, Fei Teng, Min Zhang, et al.. (2024). Semi-Supervised Dual-Stream Self-Attentive Adversarial Graph Contrastive Learning for Cross-Subject EEG-Based Emotion Recognition. IEEE Transactions on Affective Computing. 16(1). 290–305. 24 indexed citations

Ni, Dong, et al.. (2024). Recursive Deformable Pyramid Network for Unsupervised Medical Image Registration. IEEE Transactions on Medical Imaging. 43(6). 2229–2240. 33 indexed citations

Lin, Di, et al.. (2023). Non-iterative scribble-supervised learning with pacing pseudo-masks for medical image segmentation. Expert Systems with Applications. 238. 122024–122024. 8 indexed citations

Yang, Xin, Yuhao Huang, Zehui Lin, et al.. (2022). HASA: Hybrid architecture search with aggregation strategy for echinococcosis classification and ovary segmentation in ultrasound images. Expert Systems with Applications. 202. 117242–117242. 11 indexed citations

Liang, Jiamin, Xin Yang, Yuhao Huang, et al.. (2022). Sketch guided and progressive growing GAN for realistic and editable ultrasound image synthesis. Medical Image Analysis. 79. 102461–102461. 68 indexed citations

Li, Keyu, Yangxin Xu, Jian Wang, et al.. (2021). Image-Guided Navigation of a Robotic Ultrasound Probe for Autonomous Spinal Sonography Using a Shadow-aware Dual-Agent Framework. arXiv (Cornell University). 27 indexed citations

10.

Hu, Xindi, Limin Wang, Xin Yang, et al.. (2021). Joint Landmark and Structure Learning for Automatic Evaluation of Developmental Dysplasia of the Hip. IEEE Journal of Biomedical and Health Informatics. 26(1). 345–358. 15 indexed citations

11.

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

12.

Cheng, Jun, Zhi Han, Rohit Mehra, et al.. (2020). Computational analysis of pathological images enables a better diagnosis of TFE3 Xp11.2 translocation renal cell carcinoma. Nature Communications. 11(1). 1778–1778. 58 indexed citations

13.

Lei, Baiying, Peng Yang, Feng Zhou, et al.. (2019). Neuroimaging Retrieval via Adaptive Ensemble Manifold Learning for Brain Disease Diagnosis. IEEE Journal of Biomedical and Health Informatics. 23(4). 1661–1673. 14 indexed citations

14.

Wang, Yi, Na Wang, Min Xu, et al.. (2019). Deeply-Supervised Networks With Threshold Loss for Cancer Detection in Automated Breast Ultrasound. IEEE Transactions on Medical Imaging. 39(4). 866–876. 127 indexed citations

15.

Liu, Shengfeng, Yi Wang, Xin Yang, et al.. (2019). Deep Learning in Medical Ultrasound Analysis: A Review. Engineering. 5(2). 261–275. 521 indexed citations breakdown →

16.

Zhou, Xu, Rafael Molina, Yi Ma, Tianfu Wang, & Dong Ni. (2019). Parameter-Free Gaussian PSF Model for Extended Depth of Field in Brightfield Microscopy. IEEE Transactions on Image Processing. 29. 3227–3238. 5 indexed citations

17.

Li, Hang, Xinzi He, Feng Zhou, et al.. (2018). Dense Deconvolutional Network for Skin Lesion Segmentation. IEEE Journal of Biomedical and Health Informatics. 23(2). 527–537. 124 indexed citations

18.

Li, Jing, Yi Wang, Baiying Lei, et al.. (2017). Automatic Fetal Head Circumference Measurement in Ultrasound Using Random Forest and Fast Ellipse Fitting. IEEE Journal of Biomedical and Health Informatics. 22(1). 215–223. 72 indexed citations

19.

Gao, Yu, Hongzhao Li, Xin Ma, et al.. (2016). KLF6 Suppresses Metastasis of Clear Cell Renal Cell Carcinoma via Transcriptional Repression of E2F1. Cancer Research. 77(2). 330–342. 63 indexed citations

20.

Ni, Dong, Xin Ma, Yu Gao, et al.. (2014). Downregulation of FOXO3a Promotes Tumor Metastasis and Is Associated with Metastasis-Free Survival of Patients with Clear Cell Renal Cell Carcinoma. Clinical Cancer Research. 20(7). 1779–1790. 107 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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