World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
9858
World Ranking
6158
National Ranking
813

Overview

Dong Ni is affiliated with Shenzhen University in China and has contributed extensively to the fields of medicine and computer science. Their research primarily spans computer vision and pattern recognition, radiology, nuclear medicine and imaging, artificial intelligence, pediatrics, perinatology and child health, and biomedical engineering.

The scientist's research focuses on several main topics, including:

  • AI in cancer detection
  • Radiomics and machine learning in medical imaging
  • Medical image segmentation techniques
  • Domain adaptation and few-shot learning
  • Advanced neural network applications
  • Fetal and pediatric neurological disorders
  • Generative adversarial networks and image synthesis

Dong Ni has published recent papers in notable journals, illustrating ongoing contributions to medical image analysis and related domains. These papers include:

  • "A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging" (2020), Medical Image Analysis
  • "Segment anything model for medical images?" (2023), Medical Image Analysis
  • "Sketch guided and progressive growing GAN for realistic and editable ultrasound image synthesis" (2022), Medical Image Analysis
  • "Boundary-rendering network for breast lesion segmentation in ultrasound images" (2022), Medical Image Analysis
  • "Bio-inspired lubricant drug delivery particles for the treatment of osteoarthritis" (2020), Nanoscale

Frequently, they have collaborated with a core group of coauthors which includes Xin Yang, Yuhao Huang, Ruobing Huang, Wufeng Xue, and Haoran Dou, reflecting sustained research partnerships.

Their work has been published most regularly in the following venues:

  • arXiv (Cornell University)
  • Medical Image Analysis
  • Medical Physics
  • Ultrasound in Medicine & Biology
  • IEEE Transactions on Medical Imaging

Best Publications

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

    Jie Zhi Cheng;Dong Ni;Yi Hong Chou;Jing Qin

  • Deep Learning in Medical Ultrasound Analysis: A Review

    Shengfeng Liu;Yi Wang;Xin Yang;Baiying Lei

  • A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging.

    Zhaohan Xiong;Qing Xia;Zhiqiang Hu;Ning Huang

  • Standard Plane Localization in Fetal Ultrasound via Domain Transferred Deep Neural Networks

    Hao Chen;Dong Ni;Jing Qin;Shengli Li

  • Accurate Segmentation of Cervical Cytoplasm and Nuclei Based on Multiscale Convolutional Network and Graph Partitioning

    Youyi Song;Ling Zhang;Siping Chen;Dong Ni

  • Melanoma Recognition in Dermoscopy Images via Aggregated Deep Convolutional Features

    Zhen Yu;Xudong Jiang;Feng Zhou;Jing Qin

  • Accurate Cervical Cell Segmentation from Overlapping Clumps in Pap Smear Images

    Youyi Song;Ee-Leng Tan;Xudong Jiang;Jie-Zhi Cheng

  • FUIQA: Fetal Ultrasound Image Quality Assessment With Deep Convolutional Networks

    Lingyun Wu;Jie-Zhi Cheng;Shengli Li;Baiying Lei

  • Automatic Fetal Ultrasound Standard Plane Detection Using Knowledge Transferred Recurrent Neural Networks

    Hao Chen;Qi Dou;Dong Ni;Jie-Zhi Cheng

  • Ultrasound Standard Plane Detection Using a Composite Neural Network Framework

    Hao Chen;Lingyun Wu;Qi Dou;Jing Qin

  • Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound

    Yi Wang;Dong Ni;Haoran Dou;Xiaowei Hu

  • Deeply-Supervised Networks With Threshold Loss for Cancer Detection in Automated Breast Ultrasound

    Yi Wang;Na Wang;Min Xu;Junxiong Yu

  • Automatic Localization and Identification of Vertebrae in Spine CT via a Joint Learning Model with Deep Neural Networks

    Hao Chen;Chiyao Shen;Jing Qin;Dong Ni

  • Dense Deconvolutional Network for Skin Lesion Segmentation

    Hang Li;Xinzi He;Feng Zhou;Zhen Yu

  • Automatic Scoring of Multiple Semantic Attributes With Multi-Task Feature Leverage: A Study on Pulmonary Nodules in CT Images

    Sihong Chen;Jing Qin;Xing Ji;Baiying Lei

  • Reversible watermarking scheme for medical image based on differential evolution

    Baiying Lei;Ee-Leng Tan;Siping Chen;Dong Ni

  • Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound

    Yi Wang;Haoran Dou;Xiaowei Hu;Lei Zhu

  • A deep learning based framework for accurate segmentation of cervical cytoplasm and nuclei.

    Youyi Song;Ling Zhang;Siping Chen;Dong Ni

  • Towards Automated Semantic Segmentation in Prenatal Volumetric Ultrasound

    Xin Yang;Lequan Yu;Shengli Li;Huaxuan Wen

  • Relational-Regularized Discriminative Sparse Learning for Alzheimer’s Disease Diagnosis

    Baiying Lei;Peng Yang;Tianfu Wang;Siping Chen

  • Deep Attentional Features for Prostate Segmentation in Ultrasound

    Yi Wang;Zijun Deng;Xiaowei Hu;Lei Zhu;Lei Zhu

Frequent Co-Authors

Tianfu Wang
Tianfu Wang Shenzhen University
Baiying Lei
Baiying Lei Shenzhen University
Pheng-Ann Heng
Pheng-Ann Heng Chinese University of Hong Kong
Jing Qin
Jing Qin Hong Kong Polytechnic University
Feng Zhou
Feng Zhou University of Michigan–Ann Arbor
Dinggang Shen
Dinggang Shen ShanghaiTech University
Lequan Yu
Lequan Yu University of Hong Kong
Hao Chen
Hao Chen Chinese University of Hong Kong
Yuanjin Zhao
Yuanjin Zhao Southeast University
Qi Dou
Qi Dou Chinese University of Hong Kong

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online education can open new doors for students with various backgrounds and academic histories. Those seeking flexible options might consider an online computer science degree, which offers accelerated pathways for rapid skill development and entry into technology careers.

If a traditional academic track has been a challenge, there are reputable college with low gpa options that provide quality education and support for students aiming to improve their standing and job prospects.

Career pathways in computer science are increasingly interdisciplinary. For example, a background in technology pairs well with environmental fields. Those interested in sustainability can pursue an environmental engineering degree online, which prepares graduates to tackle today’s environmental challenges with cutting-edge tech skills.

Finally, combining technical expertise with other fields leads to diverse opportunities, such as unique jobs with elementary education and environmental science degree. This empowers graduates to contribute meaningfully in education, research, and green industries.

Best Scientists Citing Dong Ni

Trending Scientists

Recently Published Articles