World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
43
Citations
6359
World Ranking
6262
National Ranking
1182

Overview

Qinghua Huang is affiliated with Northwestern Polytechnical University in China and has a research profile spanning medicine and computer science.

Their work includes contributions to a range of topics suitable for interdisciplinary study, particularly in medical imaging and artificial intelligence. Main topics covered in their publications include:

  • Radiomics and Machine Learning in Medical Imaging
  • AI in cancer detection
  • Energy, Environment, Economic Growth
  • Medical Image Segmentation Techniques
  • Advanced Image Fusion Techniques
  • Medical Imaging and Analysis
  • Cerebrovascular and Carotid Artery Diseases

The researcher's fields of study predominantly lie in Medicine and Computer Science, with subfields focusing on:

  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Computer Vision and Pattern Recognition
  • Molecular Biology
  • Biomedical Engineering

Qinghua Huang has authored papers published in several frequent venues, including:

  • Neurocomputing
  • Biomedical Signal Processing and Control
  • Pattern Recognition
  • Computers in Biology and Medicine
  • SSRN Electronic Journal

Frequent coauthors who appear alongside Huang in publications include:

  • Wei Wang
  • Longzhong Liu
  • Xuelong Li
  • Zhenkun Lu
  • Cui Yang

Examples of recent papers featuring or relating to Qinghua Huang's research work are:

  • Segmentation of breast ultrasound image with semantic classification of superpixels, 2020, Medical Image Analysis
  • Quantity or quality? The impacts of environmental regulation on firms' innovation-Quasi-natural experiment based on China's carbon emissions trading pilot, 2020, Technological Forecasting and Social Change
  • Segmentation information with attention integration for classification of breast tumor in ultrasound image, 2021, Pattern Recognition
  • A Gated Recurrent Network With Dual Classification Assistance for Smoke Semantic Segmentation, 2021, IEEE Transactions on Image Processing
  • Modality-specific and shared generative adversarial network for cross-modal retrieval, 2020, Pattern Recognition

Best Publications

  • A Review on Real-Time 3D Ultrasound Imaging Technology.

    Qinghua Huang;Zhaozheng Zeng

  • An optical coherence tomography (OCT)-based air jet indentation system for measuring the mechanical properties of soft tissues.

    Yan-Ping Huang;Yong-Ping Zheng;Shu-Zhe Wang;Zhong-Ping Chen

  • Sonomyography: Monitoring morphological changes of forearm muscles in actions with the feasibility for the control of powered prosthesis

    Yong-Ping Zheng;Man-fai Chan;Jun Shi;Xin Chen

  • Breast ultrasound image segmentation: a survey

    Qinghua Huang;Qinghua Huang;Qinghua Huang;Yaozhong Luo;Qiangzhi Zhang

  • Robotic Arm Based Automatic Ultrasound Scanning for Three-Dimensional Imaging

    Qinghua Huang;Jiulong Lan;Xuelong Li

  • Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey.

    Qinghua Huang;Fan Zhang;Xuelong Li

  • Assessment of muscle fatigue using sonomyography: muscle thickness change detected from ultrasound images.

    Jun Shi;Yong-Ping Zheng;Xin Chen;Qing-Hua Huang

  • Segmentation of breast ultrasound image with semantic classification of superpixels.

    Qinghua Huang;Yonghao Huang;Yaozhong Luo;Feiniu Yuan

  • A novel feature extraction method using Pyramid Histogram of Orientation Gradients for smile recognition

    Yang Bai;Lihua Guo;Lianwen Jin;Qinghua Huang

  • Development of a portable 3D ultrasound imaging system for musculoskeletal tissues.

    Qing-Hua Huang;Yong-Ping Zheng;Min-Hua Lu;Zheru George Chi

  • On Combining Biclustering Mining and AdaBoost for Breast Tumor Classification

    Qinghua Huang;Yongdong Chen;Longzhong Liu;Dacheng Tao

  • Deep smoke segmentation

    Feiniu Yuan;Feiniu Yuan;Lin Zhang;Lin Zhang;Xue Xia;Boyang Wan

  • Segmentation information with attention integration for classification of breast tumor in ultrasound image

    Yaozhong Luo;Qinghua Huang;Xuelong Li

  • A robust graph-based segmentation method for breast tumors in ultrasound images.

    Qing Hua Huang;Su Ying Lee;Long Zhong Liu;Min Hua Lu

  • Automatic segmentation of breast lesions for interaction in ultrasonic computer-aided diagnosis

    Qinghua Huang;Feibin Yang;Longzhong Liu;Xuelong Li

  • Dynamic monitoring of forearm muscles using one-dimensional sonomyography system.

    Jing Yi Guo;Yongping Zheng;Qing Hua Huang;Xin Chen

  • GA-SIFT: A new scale invariant feature transform for multispectral image using geometric algebra

    Yanshan Li;Weiming Liu;Xiaotang Li;Qinghua Huang

  • Fully Automatic Three-Dimensional Ultrasound Imaging Based on Conventional B-Scan

    Qinghua Huang;Bowen Wu;Jiulong Lan;Xuelong Li

  • A Wave-Shaped Deep Neural Network for Smoke Density Estimation

    Feiniu Yuan;Lin Zhang;Xue Xia;Qinghua Huang

  • A Gated Recurrent Network With Dual Classification Assistance for Smoke Semantic Segmentation

    Feiniu Yuan;Lin Zhang;Xue Xia;Qinghua Huang

  • Personalized video recommendation through tripartite graph propagation

    Bisheng Chen;Jingdong Wang;Qinghua Huang;Tao Mei

Frequent Co-Authors

Xuelong Li
Xuelong Li China Telecom (China)
Yong-Ping Zheng
Yong-Ping Zheng Hong Kong Polytechnic University
Lianwen Jin
Lianwen Jin South China University of Technology
Dacheng Tao
Dacheng Tao Nanyang Technological University
Tao Mei
Tao Mei Jingdong (China)
Ling Qin
Ling Qin Chinese University of Hong Kong
Tianfu Wang
Tianfu Wang Shenzhen University
Alan Wee-Chung Liew
Alan Wee-Chung Liew Griffith University
Jingdong Wang
Jingdong Wang Baidu (China)
Hong Yan
Hong Yan City 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:

Best Scientists Citing Qinghua Huang

Trending Scientists