A5024619778- COVID-19 diagnosis using AI
- AI in cancer detection
- Anomaly Detection Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- Advanced Image Fusion Techniques
- Advanced Image and Video Retrieval Techniques
- Qualitative Comparative Analysis Research
- Data-Driven Disease Surveillance
- Video Analysis and Summarization
- Photoacoustic and Ultrasonic Imaging
- Color Science and Applications
- Video Surveillance and Tracking Methods
- Electromagnetic Scattering and Analysis
- Advanced Computing and Algorithms
- Nursing Roles and Practices
- Remote-Sensing Image Classification
- Embedded Systems Design Techniques
- Genetics, Bioinformatics, and Biomedical Research
- Digital Imaging for Blood Diseases
- COVID-19 epidemiological studies
- Neural Networks and Applications
- Face and Expression Recognition
Huazhong University of Science and Technology
2024
Shantou University
2021
Currently, the new coronavirus disease (COVID-19) is one of biggest health crises threatening world. Automatic detection from computed tomography (CT) scans a classic method to detect lung infection, but it faces problems such as high variations in intensity, indistinct edges near infected region and noise due data acquisition process. Therefore, this article proposes COVID-19 pulmonary infection segmentation depth network referred Attention Gate-Dense Network- Improved Dilation...
Abstract The diversity and large scale of multi-view data have brought more significant challenges to conventional clustering technology. Recently, has received widespread attention because it can better use different views’ consensus complementary information improve performance. Simultaneously, many researchers proposed various algorithms reduce the computational complexity accommodate demands large-scale clustering. However, current reviews do not summarize from perspective reducing...
Breast ultrasound examination is a routine, fast, and safe method for clinical diagnosis of breast tumors. In this paper, classification based on multi-features support vector machines was proposed tumor diagnosis. Multi-features are composed characteristic features deep learning images. Initially, an improved level set algorithm used to segment the lesion in images, which provided accurate calculation features, such as orientation, edge indistinctness, characteristics posterior shadowing...